Grid and Pervasive Computing

Cloud Computing shapes the IS Outsourcing landscape and enables new flexible delivery models. It has become a fast growing and non-transparent market with many providers, including heterogeneous service portfolios and business models, especially for Software as a Service (SaaS). Many researchers focus exclusively on the technical aspects of Cloud Computing and ignore the business perspective. Unfortunately, the terms Cloud Computing and SaaS are not defined clearly and face customers with several challenges related to the decision-making process. This article explores the nature of SaaS from a business point of view and examines 100 providers in order to gain new insights about the transparency of their service offerings. A cluster analysis is conducted to examine dependencies between different provider information. The results indicate that only basic data like contact information, provider profile and service functionality are provided by all vendors, whereas pricing, support and security information are only covered by half of the providers.

Accounting is an essential part of distributed computing infrastructures, regardless whether these are more service-driven like Clouds or more computing oriented like traditional Grid Computing environments. Those infrastructures have evolved over more than the last decade and additional. beside the further development towards service-oriented architectures, the business aspect of especially Cloud Computing solutions becomes more and more relevant. In this paper we focus on user-centric aspects like privacy preserving methods to hide the users behaviour and to collect only necessary information for billing, under the assumption that an accounting system has to be integrated in the computing infrastructure and that a central interface is still desirable for billing and financial clearing.

Existing popular virtual machine monitors like Xen, VMware, etc. are mostly for virtualization of one single physical node. There are few researches on virtual machine monitor for distributed cross-node cloud computing resources integration. This paper introduces a novel distributed virtual machine monitor (CloudDVMM). We present its theoretical model, architecture and key technologies. Experiments and comparisons with existing researches show that our CloudDVMM achieves merits in architecture, extensibility, etc. and is promising for meeting the integration requirements of distributed virtual computing and cloud computing environments.

Cloud Computing can be viewed as a computing model containing a pool of resources and Internet based application services. Cloud makes on-demand delivery of these computational resources (data, software and infrastructure) among multiple services via a computer network. An infrastructure-as-a-service cloud system provides computational capacities to remote users. In present scenario, most of the Infrastructure as a Service (IaaS) Clouds use simple resource allocation policies like immediate and best effort. In private cloud, since the resources are limited, maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. Hence efficient scheduling is needed which is a major challenge in satisfying the user’s requirement (QoS). In this paper, we propose an advanced reservation technique with backfilling in scheduling policy that aims at serving the user requests by satisfying the required QoS, achieving the guaranteed service for the request by making an efficient provisioning of cloud resources.

Recommender system can help users to effectively identify interested items from a potentially overwhelming huge collection of items, and it has been shown to be very useful in many e-commerce applications. Collaborative filtering (CF), which assumes that similar users may have similar tastes, is one of the most widely used Recommender system techniques. However, one of the major weaknesses for the CF mechanism is the computational cost in computing pairwise similarity of users. This paper attempts to tackle the computational problem of all pairs similarity using the MapReduce technique in the Hadoop framework. We give an overview of our development on using a parallel filtering algorithm to improve the performance of a personal ontology based recommender system for digital library. The experimental results show that the proposed algorithm can indeed scale out the recommender systems for all pairs search.

With the recent advancements in distributed systems, Cloud computing has emerged as a model for enabling convenient, on-demand network access to a shared resource pool of configurable elements such as (networks, servers, storage, applications, and services). Various applications are developed and deployed into the Cloud following the layered architecture. The layered approach includes infrastructure, virtualization, application, platform and client tiers. Provenance (the meta-data), is the information that helps cloud providers and users to determine the derivation history of a data product, starting from its origin. Each layer in the Cloud has its own provenance data and generally, provenance data for each layer address different audience. For example, Cloud providers are interested in the infrastructure provenance data to verify the high utilization of resources through audit trials. Cloud users on the other hand are interested in the performance of the deployed application and the verification of experiments. In this paper, we present various queries regarding the provenance data for different layers of Cloud. Hereby, we integrate the provenance data from individual layers and highlight the importance of integrated provenance. We also outline the relationship between various layers of the Cloud by using the integrated provenance.

In this paper, we propose a new OpenCL toolkit called JCL for heterogeneous clusters. Using this toolkit, users can make use of multiple remote heterogeneous processors including CPUs and GPUs for the execution of their OpenCL programs. Since load balance is an important issue for the performance of the user programs executed by heterogeneous processors, the proposed toolkit provides users with a set of load-balancing functions to automatically adjust the amount of data assigned to each processor according to processor’s computation power. We have evaluated the performance of the proposed toolkit in this paper. Our experimental result shows that the proposed toolkit really can enable the test programs to effectively exploit heterogeneous processors for enhancing their execution performance.

MapReduce is an effective tool for processing large amounts of data in parallel using a cluster of processors or computers. One common data processing task is the join operation, which combines two or more datasets based on values common to each. In this paper, we present a network aware multi-way join for MapReduce(NAMM) that improves performance by redistributing the workload amongst reducers. NAMM achieves this by redistributing tuples directly between reducers with an intelligent network aware algorithm. We show that our presented technique has significant potential to minimize the time required to join multiple datasets.

Web applications play a major role in various enterprise and cloud services. With the popularity of social networks and with the speed at which information can be disseminate around the globe, online systems need to face ever-growing, unpredictable peak load events.

Auto-scaling

technique provides on-demand resources according to workload in cloud computing system. However, most of the existing solutions are subject to some of the following constraints: (1) replying on user provided scaling metrics and threshold values, (2) employing the simple Majority Vote scaling algorithm, which is ineffective for scaling Web applications, and (3) lack of capability for predicting workload changes. In this work, we propose an effective auto-scaling strategy, called

Work-load Based

scaling algorithm, for Web applications. Our proposed scaling strategy is not subject to the aforementioned constraints, and can respond to fluctuated workload and sudden workload change in a short time without relying on over-provisioning of resources. We also propose a new method for analyzing the trend of workload changes. This trend analysis method provides useful information to the scaling algorithm to avoid unnecessary scaling actions, which in turn shortens the response time of requests. The experiment results show that the hybrid

Workload Based

and

trend analysis

method keeps response time within 2 seconds even when facing sudden workload change.

Cloud Computing as a service-on-demand architecture has grown in importance over the previous few years. One driver of its growth is the ever increasing amount of data which is supposed to outpace the growth of storage capacity. In this way public cloud storage services enable organizations to manage their data with low operational expenses. However, the benefits of cloud computing come along with challenges and open issues such as security, reliability and the risk to become dependent on a provider for its service. In general, a switch of a storage provider is associated with high costs of adapting new APIs and additional charges for inbound and outbound bandwidth and requests. In this paper, we describe the design, architecture and implementation of Cloud-RAID, a system that improves availability, confidentiality and integrity of data stored in the cloud. To achieve this objective, we encrypt user’s data and make use of the RAID-technology principle to manage data distribution across cloud storage providers. The data distribution is based on users’ expectations regarding providers geographic location, quality of service, providers reputation, and budget preferences. We also discuss the security functionality and reveal our observations on the utility and users benefits from using our system. Our approach allows users to avoid vendor lock-in, and reduce significantly the cost of switching providers.

Supercomputer prices on one hand and the need for vast computational resources on the other hand, led to the development of network computing resources were under name Grid. For optimal use of the capabilities of large distributed systems, the need for effective and efficient scheduling algorithms is necessary. For reduction of total completion time and improvement of load balancing, many algorithms have been implemented. In this paper, we propose new scheduling algorithm based on well known task scheduling algorithms, Min-Min. The proposed algorithm tries to use the advantages of this basic algorithm and avoids its drawbacks. To achieve this, the proposed algorithm firstly like Min-Min estimating of the completion time of the tasks on each of resources and then selects the appropriate resource for scheduling. The experimental results show that the proposed algorithm improved total completion time of scheduling in compared to Min-Min algorithm.

Nowadays, cloud computing has become one of the major issues on the progress of computer science. Applying Diskless Remote Booting (DRB) System to cloud computing has potential to reduce energy consumption and enhance Maintainability. Previous research has introduced homogeneous DRB system which consists of compute nodes with the same hardware and software configuration. However, in the homogeneous DRB system, adding a new node requires the same hardware and software configuration. In this paper, we propose a heterogeneous DRB system that allows compute nodes to have various hardware and software configurations. Moreover, the proposed scheme is equipped with hypervisor to each compute node, so that every compute node provides a virtual environment for its end-users. The experiment results show our approach can run a number of compute nodes with various hardware and software configurations concurrently. Furthermore, the proposed scheme has outstanding benefits to energy saving with negligible performance loss.

Replica management has become a hot research topic in storage systems. This paper presents a dynamic replica management strategy based on response time, named RTRM. RTRM strategy consists of replica creation, replica selection, and replica placement mechanisms. RTRM sets a threshold for response time, if the response time is longer than the threshold, RTRM will increase the number of replicas and create new replica. When a new request comes, RTRM will predict the bandwidth among the replica servers, and make the replica selection accordingly. The replica placement refers to search new replica placement location, and it is a NP-hard problem. Based on graph theory, this paper proposes a reduction algorithm to solve this problem. The simulation results show that RTRM strategy performs better than the five built-in replica management strategies in terms of network utilization and service response time.

As Hadoop becomes a popular distributed programming framework for processing large data on its distributed file system (HDFS), demands for secure computing and file storage grow quickly. However, the current Hadoop does not support encryption of storing HDFS blocks, which is a fundamental solution for secure Hadoop. Therefore, we propose a secure Hadoop architecture by adding encryption and decryption functions in HDFS. We have implemented secure HDFS by adding the AES encrypt/decrypt class to

CompressionCodec

in Hadoop. From experiments with a small Hadoop testbed, we have shown that the representative MapReduce job on encrypted HDFS generates affordable computation overhead less than 7%.

The cloud computing is a computing paradigm that users can rent computing resources from service providers as much as they require. A spot instance in cloud computing helps a user to utilize resources with less expensive cost, even if it is unreliable. When a user performs tasks with unreliable spot instances, failures inevitably lead to the delay of task completion time and cause a seriously deterioration in the QoS of users. To solve the problem, we propose the VM migration scheme to reduce the job waiting time. And in this scheme we use our previously proposed checkpointing method. When a running instance occurs the out-of-bid situation (failure), the VM on the failed instance is to a new instance. Our proposed VM migration scheme reduces the rollback time and the task waiting time when an instance occur the out-of-bid situation. The simulation results show that our scheme achieves performance improvements in the task execution time of 68.94%, 68.61%, and 46.35% compared with the hour-boundary checkpointing scheme, the rising edge-driven checkpointing scheme, and our previously proposed checkpointing scheme., respectively Further, our scheme outperforms the existing schemes in terms of the reduction the total costs per spot instances for a user’s bid.

Natural disaster management needs to deal with large amount of data originated from various organizations and mass people. Therefore, a scalable environment provided with flexible information access, easy communication and real time collaboration from all types of computing devices, including mobile handheld devices, such as smart phones, PDAs and iPads are essential. It is mandatory that the system must be accessible, scalable, and transparent from location, migration and resources. In this paper a framework has been proposed in order to design a Cloud based workflow management system along with scheduler for natural disaster management system, where in Cloud environment, web service and EC2 technologies have been leveraged in order to design the Cloud based workflow model for disaster management system.

The scene of the computational sciences has considerably changed during the last years. Today, new emerging Desktop grid and Cloud e-infrastructure have a considerable potential to be adopted and used in large scale to exploit thousands of CPUs power to run both scientific and commercial applications. This paper targets scientists and programmers who need to accelerate their scientific research by running their applications on distributed Grid/Cloud infrastructures. We present a hybrid Grid/Cloud platform used to deploy a phylogeny application called MetaPIGA. The aim is to combine the advantages of Grid and Cloud architectures in order to set up a robust, reliable and open platform. We propose two scenarios.

Several Cloud computing business models have been developed and implemented, including dynamic pricing schemes. This paper extends the known concepts of revenue management to the specific case of Cloud computing from two perspectives. First, we propose system architecture for Cloud service providers for combining demand-based pricing and scheduling. Second, a comparison of two yield management methods for cloud computing has been compared: Limited Discount Period Algorithm and VM Reservation Level Algorithm. By taking advantage of demand estimation, the two algorithms find the optimum number of VMs that are sold at full price and the optimum time period before the allocation when the prices should change. Simulation results show that both yield management methods outperform static pricing models and the algorithms perform differently considering the deviation of demand.

For comparing Java virtual machines targeting smart systems such as wireless sensor nodes, a list of qualitative and quantitative criterions is proposed. The open source JVMs Takatuka and Darjeeling are then compared by architecture and features. The JVM runtime properties are benchmarked on an MSP430-based test platform. Results show that Takatuka is the mature, feature-rich, multi-purpose JVM near J2ME with a 50% advantage in Java byte code size. Darjeeling fits well for tiny, focused applications and offers a runtime performance bonus of up to a factor of six.

In order to research the law of public opinion formation of microblog from the perspective of complex systems, agent’s action rules are put up. Opinion updated equation is amended in accordance with affinity of participants of topics in microblog. Combined with the network topology of micro-blogging topics participants, the process of opinion formation is simulated. Disordered individual opinions emerged out of the system of ordering turns out to be the result, which is, forming public opinion. Examples are used to verify the validity of the model. It will make exploratory groundwork for further media dissemination and monitoring of public opinion online.

Virtualization is a process of manifestation of the logical group or subset of computer resources in computer science. However, virtualization we mentioned in this paper is “platform virtualization”. It is VM (virtualization machine) as we often named. Benefits of virtualization are numerous and it is considered to be a previous procedure to learn before adapting cloud technology for the enterprise. The constructed environment in this paper has implemented virtualization for further experiment. The main subject of this paper is how to construct virtualization in the cloud with integration of KVM and OpenNebula for users. It provides private cloud solutions for enterprises or organizations and focuses on IaaS of three services in cloud. This system can reduce the complexity of accessing the cloud resources through users’ interface. That is to say it is easy to manage deployment of the VMs by the web-based users’ interface. The paper contains of live migration data measurement, comparison of physical machines and virtual machines, and analysis results. In the experimental environment, we prove that the performance of full virtualization is closer to the physical machine as well.

Almost cloud service providers are having their own architectures for providing a variety of cloud services to their customers, cloud service clients. These various architectures and services increase the complexity of security management policies, frameworks, and systems, because they would require different aspects of security solutions for their own architectures and services. Consequently, such compatibility issues make us difficult to design a common security framework, security management system, or security evaluation system. Recognizing the need to solve such issues, we analyze common security elements to be required for cloud computing virtualization, and identify requirements for information protection in this paper. We also identify possible threats that may occur depending on different functions and roles over the cloud virtualization environments, and define security elements and requirements to deal with those issues. We show a set of common directions or approaches to prevent any possible treats to cloud computing, and provide more efficient and systematic method of managing and operating cloud computing system.

During last few years we have witnessed a steady increase in medicine use for healthcare. The medicine experiences rated by other patients have huge potential to empower people to make more informed decisions. While the majority of previous research focused on rating prediction and recommendations on E-Commerce field, the area of healthcare or medical treatments has been rarely handled. Moreover, the geographical and temporal factors were not considered in their recommendation mechanisms. The rapid development of mobile devices, wireless networks, smart phones and ubiquitous wireless connections enable people to build and maintain mobile social interactions and relationships. In this paper, we identify and formalize the significant problem that exploits the over-the-counter medicine rating prediction and recommendation in mobile social networks. Then we devise the recommendation model and develop corresponding prototype of iDrug, reflecting a solution scheme of medicine rating prediction and recommendation in mobile social networks to increase the information accessibility for people’s decision support.

The web browser has become one of the most important and frequently used computer programs that people use. The web browser has effectively assumed the role of an operating system. Yet there have been predictions that the web browser and the Web itself will effectively die. More specifically, it has been argued that the web browser will lose the battle against native, custom built web apps. In this paper we predict that the web browser may indeed disappear but for entirely different reasons. We present a concept and implementation of a cloud browser that moves the users’ browser sessions and the user interface chrome of the web browser to the cloud. The benefits of a cloud browser are especially valuable to those people who use a plethora of web-connected devices, allowing the same web pages and applications to be used flexibly – and even simultaneously – from different devices.

Current educational games vary in how they present content, how they evaluate recently learned topics, and how student-teacher interaction is mediated. And while some treat educational games as an extra tool, others as virtual environments for practice, and some others as a replacement of the teacher, the areas of knowledge these are best suited for are usually abstract and technical. We present a method adapted from Visual Novels (VN), a sub-genre of Adventure Games born in Japan, that makes use of attractive characters, narrative engagement, puzzles and other interactive features to maintain user interest while submerging players in complex stories. With this our approach we are able to teach theoretical topics through discernment in multiple game scenarios, increasing knowledge and maintaining entertainment value. We show our results from experiments with a VN for Smart Pads we developed with Participatory Design, discuss our findings, limitations and talk about our future work.

In Heterogeneous Wireless Networks (HetNets), different overlappedRadio Access Networks (RANs) can coexist with each other in the same geographical area with the goal to provide high rates pervasive access for mobile users via multi-mode terminals. This paper addresses the problem of initial RAN selection in HetNets with two co-located wireless networks which supports two different service classes. The framework of Semi-Markov Decision Process (SMDP) is used to formulate the problem as a Joint Call Admission Control (JCAC) optimization problem that involves the design of a total cost function that weights two criteria: the blocking cost and the energy consumption cost. Simulation results are provided, showing that our JCAC optimal policy often selects the less energy consuming RAN when more weight (50% or more) is given to the energy consumption cost in the total cost function.

In this paper we address the problem of deploying Desktop Grid (DG) middleware when we need it, where we need it, and on any device. One option is to put DG middleware into the cloud but at the condition that the code is suited for integration into the cloud. DG middleware were not generally developed with this option in mind. We propose an advanced prototype for a DG middleware able to run on small devices, i.e. smartphones and tablets as well as on more traditional computing devices (PCs). We explain, based on our experience, that the integration of existing DG middleware for small devices may be extraordinary challenging, resulting in rethinking the DG paradigm in terms of interactions between the components. We adopt a user-centric point of view in considering that the DG technology should be as simple as possible in its use. In another words, we are exploring the ways to offer DG as a service. Our prototype serves to illustrate our techniques and methodologies and to get a feedback and an analysis of our design.

This paper proposed the Greenhouse Control System (GCS) for high adaptability in greenhouse control devices and application services. The system is divided into the Greenhouse Control Engine (GCE) and the Crop Growth Engine (CGE). The GCE consists of Data Aggregator (DA), Greenhouse Information Storage (GIS), and Greenhouse Control Agent (GCA). The GCA includes Information Analyzer (IA), Control Device Selector (CDS), and Greenhouse Model (GM). The GCA selects control devices by referencing the aggregated greenhouse’s information and the climate set-points. In this process, we apply the arbitrary greenhouse model to the GCA. And the CGE consists of Crop Status Information Storage (CSIS) and Crop Growth Agent (CGA). The CGA decides the climate set-points by applying the arbitrary crop growth model. The CGA has Crop Condition Predictor (CCP), Environment Set-points Decisioner (ESD), and Crop Growth Model (CGM). By interacting of each component, this system provides with the greenhouse control service and the crop growth prediction service. The greenhouse control service monitors the inside and outside climate of a greenhouse and controls the control devices of a greenhouse on the GCA. The crop growth prediction service predicts the crop growth status by considering the meteorological data and business data. Finally we showed the executing result by implementing the GCS.

Unstructured Peer-to-Peer (P2P) overlays are the most widely used topologies in P2P systems because of their simplicity and very limited control overhead. A P2P overlay specifies the logical connections among peers in a network. Such logical links define the order in which peers are queried in search for a specific resource. The most popular query routing algorithms are based on flooding, thus they do not scale well as each query generates a large amount of traffic. In this paper, we use heuristics to improve overlay search in an unstructured P2P file sharing system. The proposed heuristics effectively decide replica locations for popular resources based on the availability of computing and storage at a given peer, its neighborhood information, and the used routing strategy. Simulations performed over two different types of unstructured P2P network topologies (i.e., power law and random graphs) show significant improvements over plain flooding in terms of reduced network traffic and search time.

The mobile Virtual Private Network (MVPN) of the Internet Engineering Task Force (IETF) is not designed to support NEtwork MObility (NEMO) and is not suitable for real-time applications. Therefore, architecture and protocols to support VPN in NEMO are needed. Therefore, in this paper we propose a cost-reduced secure mobility management scheme (CE-SeMMS) that is based on session initiation protocol (SIP) and designed for real-time applications with VPN. Our scheme to support MVPN in NEMO enables the session to be well maintained during movement of the entire network. Further, in order to reduce the authentication delay time in handoff operations, the signaling time which occurs to maintain the session is shortened through our proposed handoff scheme which adopts authentication using HMAC-based one-time password (HOTP). Our performance analysis results show our proposed scheme provides improvement in average handoff performance time relative to existing schemes.

Recent advances of embedded and wireless technologies make ubiquitous wireless sensor and actuator networks (WSANs) a reality. While individual sensor nodes are relatively easy to use, the overall system behaviors are difficult to model and program. This paper presents a novel system-level software design methodology using a concurrent and reactive programming language, SystemJ, in designing distributed pervasive applications based on WSANs with no requirement of any additional middleware. A context-aware pervasive service case study, where multiple fixed and mobile IPv6-enabled WSAN nodes are deployed in an office environment for RSSI-based localization and automated lighting control based on the user location, is designed using SystemJ.

In this paper an architecture for context aware framework for mobile phones has been represented. The main goal of this proposed architecture is to enable phones to configure themselves based on self-initiated decisions which are directed by surrounding. This framework will reduce user’s manual settings configuration. This will increase the flexibility level to great extent. Finally using the proposed framework phone will be self-configured. Most of the existing work regarding context aware mobile application is mainly based on location. However in this paper we have included a variety of context aware information along with inferred activities e.g. driving, running, meeting etc. in which users are engaged. In addition power management and memory management are two most important limitations of mobile devices. In this paper these two limitations are improved to a significant stage.

In this paper, we propose additional mobility management schemes based on pointer forwarding for Proxy Mobile IPv6 (PMIPv6) networks with the aim of reducing the overall network traffic caused by mobility management and packet delivery. The proposed schemes are per-user-based, i.e., the optimal threshold of the forwarding chain length that minimizes the overall network traffic is dynamically determined for individual mobile user based on the mobility and service patterns. We show that there is an optimal threshold of the forwarding chain length given a set of parameters characterizing the specific mobility and service patterns of a mobile user. We also describe that our schemes yield significantly better performance than schemes that be applicable a static threshold to all mobile users. A comparative analysis shows that our pointer forwarding schemes outperform routing-based mobility management protocols for PMIPv6 networks.

Stream processors, with the stream programming model, have demonstrated significant performance advantages in the domains signal processing, multimedia and graphics applications, and are covering scientific applications. Jacobi iteration, which is widely used to solve partial differential equations, is an important class of scientific programs. As computers became more powerful, scientists have begun writing 3-D programs to solve PDEs. In this paper we examine the applicability of a stream processor to 3-D Jacobi iteration. In a stream processor system, the management of system resources is the programmers’ responsibility. Compared with 2-D Jacobi iteration, some new issues must be considered, since reuse along the third dimension cannot fit in on-chip memory. We first map 3-D Jacobi iteration in FORTRAN version to the stream processor in a straightforward way. We then present several optimizations, which avail the stream program for 3-D Jacobi iteration, called StreamJacobi, of various aspects of the stream processor architecture. Finally, we analyze the performance of StreamJacobi, with different scales, and the presented optimizations. The final stream program StreamJacobi is from 2.43 to 11.48 times faster than the corresponding FORTRAN programs on a Xeon processor, with the optimizations playing an important role in realizing the performance improvement.

CS (Conflict Serializability) is a recently proposed relaxer correctness criterion that can increase transactional memory’s parallelism. DDA (Distributed Dependency-Aware) model is currently proposed to implement CS in distributed STM (Software Transactional Memory) for the first time. However, its transactions detect conflicts individually via detecting cycles in PG (Precedence Graph) and cause extra runtime overhead, especially at the condition that the transactions access lots of objects or the PG is large. In this paper, we propose an approach to make each cycle in PG detected by those transactions, which construct this cycle, together in parallel way, instead of detecting cycle individually. Experimental results show that the average execution time and communication cost of all transactions, including aborted ones, in our approach, can be decreased to 76% and 78% of those in DDA respectively. Its speedup is up to 2.56× against baseDSTM, employing two-phase locking.

With system size and complexity is growing rapidly, traditional passive fault tolerance can no longer guarantee the reliability of system because of the high overhead and poor scalability of these methods. Active fault tolerance is believed to be the most important fault tolerant approach for exascale systems. Aiming at system failure prediction, this paper proposes a system logs pre-processing method using classification via sparse representation (SRCP). Adopting the idea of vectorization, SRCP removes the details of each log and generates the corresponding Vectors. It uses TF-IDF (term frequency-inverse document frequency) method to Weight each keyword which can reveal more precise information about correlation between log records. In order to improve the accuracy and flexibility of pre-processing method, log vectors are processed by sparse representation classification. For generalization purpose, SRCP does not adopt any expert system or domain knowledge. Experimental results show that, SRCP can not only achieve both outstanding precision and F-measure, but also provide a satisfactory compression ratio.

In this paper, we introduce how to write M2M applications by using INI, a programming language specified and implemented by ourselves that supports event-based style. With event-based programming, all M2M communication can be handled and scheduled. Programmers may use existing built-in events or define their own events. We apply our approach in a real M2M gateway, which allows gathering and exchanging information between sensors and machines in the network. The results shows that our work proposes a concise and elegant alternative and complement to industrial state-of-the-art languages such as Java or C/C++.

An on-line optimization method for explosives storage scheduling based on genetic algorithm is proposed to make management of explosives storage process more efficient, informative, secure, and intelligent. The information of explosives warehouse is acquired in real time by RFID technology, and an assignment strategy for the location of explosives in warehouse is proposed. The mathematical model of explosives storage optimization is constructed by analyzing operation characteristics of explosives storage and requirements, and the model is solved using the improved genetic algorithm. The simulation results show that the proposed method can improve the utilization rate of warehouse space, optimize the walking path in the process of the explosive delivery, as well as solve the operating problems under some constraints, such as the expire date of explosives.

This paper proposes a new weighted mining technique based quantity item with RFM(Recency, Frequency, Monetary) score for personalized u-commerce recommendation system under ubiquitous computing, or pervasive computing environment. Traditional association rule mining ignores the difference among the transactions. In this paper, it is necessary for us to consider the quantity of purchased data by each rank of RFM score in order to have different weights for different transactions, to generate weighted association rules through weighted mining association rules based quantity item with RFM score, and to recommend the items with high purchasability according to the threshold for creative weighted association rules with w-support, w-confidence and w-lift. To verify improved performance, we make experiments with dataset collected in a cosmetic internet shopping mall.

Live migration of Virtual Machines (VMs) has been a powerful tool to facilitate system maintenance, load balancing, fault tolerance, and power saving. In this paper, we describe the design and implementation of a novel, priority-based approach for the live migration of VM that can greatly reduce VM service downtime. Our approach is mainly used in the desktop virtual environment where there are more than one application running in the VM. Our scheme offers applications that demand short service downtime the high migration priority while applications that can tolerate long VM service downtime are assigned with the low migration priority. During the iterative copy and the stop-and-copy phases, our scheme only transfers all dirty pages that belong to the high priority applications, so the service downtime will be less than that of pre-copy. Compared with pre-copy based live migration, the proposed approach can significantly reduce 57% of the service downtime of high priority applications.

In this paper, we propose the coordinate change schemes for improving the performance of blind equalizer such as MCMA (modified constant modulus algorithm) which compensate for ISI channel effect. ISI (inter symbol interference) is generated due to user’s movement in the mobile satellite communication environment. Satellite communication systems do not use pilot signals for channel estimation. Blind equalization techniques such as MCMA are well known that it is possible to estimate and to compensate for channel without pilot signals. It is necessary to improve the blind equalizer performance. Therefore, we propose the coordinate change schemes for improve the equalization performance in 16-APSK. We confirm that this proposed method has better equalization performance than conventional MCMA.

Mobility health is an important aspect of the overall health status of a person. Many tests exist that determine the mobility health of a subject, but there are several issues associated with these tests, such as human error. Much work is being done to develop a mobility classification system which consolidates these tests, and circumvents the associated issues. Even so, many of these systems in development are complicated and lack the calculation of important postural transition measurements. The goal of this project was to remove the errors associated with current mobility tests, and to make the system as simple and energy-efficient as possible. In addition, we wanted this system to be able to detect with accuracy of over 90% six mobility states in addition to postural transition information. These goals were accomplished by using a waist-mounted triaxial accelerometer that processed data on-board using a well-developed classification algorithm.

RPC is a communication technology which has been widely used in distributed systems. It has been employed as an essential component of distributed systems. However, the performance of traditional RPC technology will be seriously decreased in high-speed network based cluster system. The main reason is that the network of cluster has many obvious features such as high bandwidth, low latency, and high reliability, etc, which are different from normal network environment. Therefore, how to improve the performance of RPC technology in cluster system has caught increasing attention.

In this paper, we have carefully studied the traditional RPC technology, which suggest that the decreasing of cluster network performance is mainly caused by the

serialization/deserialization

process of RPC technology. Thus we proposed a dedicated

serialization/deserialization

scheme which can run on homogeneous cluster system. This scheme can well improve the performance of cluster network by reducing the number of date copy operations of RPC protocol. We have evaluated our improved scheme in our real-world cluster system. And our evaluation results show that our scheme can significantly promote performance of bandwidth by up to 43% in our cluster system when the size of transmitted data block is large.

Online social networks are rapidly becoming popular for users to share, organize and locate interesting content. Users pay much attention to their close friends, those direct or two-hop friends. Users of Facebook commonly browse relevant profiles and the homepages, which are inefficient in obtaining desired information for a user due to the large amount of relevant data. In this paper, we propose a summary index with a ranking model by extending existing Bloom filter techniques, and achieve efficient full-text search over large scale OSNs to reduce inter-server communication cost and provide much shorter query latency. Furthermore, we conduct comprehensive simulations using traces from real world systems to evaluate our design. Results show that our scheme reduces the network traffic by 94.1% and reduces the query latency by 82.4% with high search accuracy.

Nowadays graphic processing unit (GPU) delivers much better performance than CPU does, and it is becoming increasingly important in high performance computing (HPC) because of its tremendous computing power. At the same time the concept of cloud computing is becoming increasingly popular. This business model suggests that GPU will be more economical because users can spend less money to rent GPUs to fit their special computing needs, rather than buying GPUs. The current practice of virtual GPU rental service is to bind a GPU to a virtual machine

statically

. As a result this static binding practice is less economical and less flexible. The goal of this paper is to design a GPU provision system that combines CUDA programs from different virtual machines and execute them

concurrently

, so as to support the concept of GPU sharing among virtual machines.

MapReduce is a programming model introduced by Google for large-scale data processing. Several studies have implemented MapReduce model on Graphic Processing Unit (GPU). However, most of them are based on the single GPU and bounded by GPU memory with inefficient atomic operations. This paper intends to develop a standalone MapReduce system, called MGMR, to utilize multiple GPUs, handle large-scale data processing beyond GPU memory limit, and eliminate serial atomic operations. Experimental results have demonstrated MGMR’s effectiveness in handling large data set.

This paper describes an approach to detecting distributed denial of services (DDoS) attacks that is based on Information theory, specifically Kolmogorov Complexity. A theorem derived using principles of Kolmogorov Complexity describes that the joint complexity measure of random strings is lower than the sum of complexities of the individual strings when the strings exhibit some correlation. However, Kolmogorov complexity is not calculable, various methods exist to measure estimates of complexity. In the viewpoint of Kolmogorov complexity, we have found out the characteristics of DDoS attacks after analyzing a lot of DDoS attack cases. We propose a new method to compute the joint complexity using Deep Packet Inspection (DPI). DPI depends on string matching process and regular expression heuristics that make a thorough investigation on the packet payloads in a search for networked application signatures. As ISPs backbone links’ speed and data volume increase rapidly, commodity hardware-based DPI systems face performance bottlenecks and the difficulty of scalability, which interferes on traffic classification accuracy dramatically. This paper introduces a lightweight DPI algorithm for an expeditious detection that can detect the presence of a DDoS in the Internet as quickly as possible in order to provide people accurate early warning information and possible reaction time for counteractions. Furthermore, it increases the exactitude of detecting DDoS and doesn’t decrease network backbone’s performance.

With the prevalence of cloud computing, many enterprise users store confidential information in the cloud servers. Therefore, the problems of data security in cloud computing are particularly important. Cloud storage service providers must offer efficient cryptography system and access control scheme to users. In recent years, some researchers proposed identity-based hierarchical key deployment model for encryption and access control in cloud computing environment. However, some of these schemes have high computing cost and do not take authentication into consideration. In this paper, we proposed a low-cost cryptography system and attribute-based access control scheme for the cloud storage environment. The simulation results and analysis show that the proposed method has lower communication and computing cost than Hierarchical Attribute-Based Encryption (HABE). Our proposed scheme can achieve the data access control via user’s attribute-based rules. It also satisfies the authentication requirements by using identity-based signature in the cloud storage environment.

Cloud computing brings novel concepts and various applications for people to use computer on theInternet, where all of above-mentioned concern with user authentication. Password is the most popular approach for user authentication in daily life due to its convenienceand simplicity. However, on Internet, user’s password is easier to suffer from distinct threats and vulnerability. First, for the purpose of easily memorizing, user often selects a weak password and reuses it between different service providers on websites. Without a doubt, an adversary will obtain access to more websites if the password is compromised. Next, an adversary can launch several methods to snatch users’ passwords such as phishing, keyloggers, and malware, and those are hard to be guarded against. In this manuscript, we propose an active one-time password (AOTP) mechanism for user authentication to overcome two abovementioned problems, password stealing and reuse, utilizing cellphone and short message service. Through AOTP, there is no need for additional tokens, card readers and drivers, or unfamiliar security procedures and user can choose any desirous password to register on all websites. Furthermore, we also give some comparison tables to present that the proposed mechanism is better than other similar works.

Data Encryption/Decryption has become an essential part of pervasive computing systems. However, executing these cryptographic algorithms often introduces a high overhead. In this paper, we select nine widely used cryptographic algorithms to improve their performance by providing hardware-assisted solutions. For each algorithm, we identify the software performance bottleneck,

i.e.,

those “hotspot functions” or “hot-blocks” which consume a substantial portion of the overall execution time. Then, based on the percentage of execution time of a specific function and its relationship with the overall algorithm, we select candidates for our hardware acceleration. We design our hardware accelerators of the chosen candidates. The results show that our implementations achieve speedups as high as 60 folds for specific functions and 5.4 for the overall algorithm compared with the performance of the software-only implementation. Through the associated hardware cost analysis, we point to an opportunity to perform these functions in an SIMD fashion.

In this paper, we propose chaotic wireless communication system using digital retrodirective array antenna (RDA) for improving security and receive performance at receiver. Chaotic modulation schemes have studied for reducing the probability of interception and interrupt. As a result, chaotic communication systems have enhanced security. But the receive performance at receiver is degraded. We propose digital RDA system based on chaotic modulation for improving the reception performance while maintaining the security. Simulation results show that to overcome degradation of reception performance in CDSK, digital RDA with array elements up to five is required compared to BPSK modulation scheme.

In the SaaS (Software as a Service) model, the sensitive data of tenants are in danger of leakage. Meanwhile there are different privacy requirements for different tenants. This paper presents a policy based customized privacy preserving mechanism which realizes the preserving of tenants’ sensitive data. Based on the requirements of the tenants and the transactions of SaaS application, we build the policy of tenants’ customized privacy preserving and fragment tenants’ sensitive data through the Related Attributes Model(RAM). Finally we realize the effective combination of unencrypted privacy preserving and SaaS application’s transaction. To avoid the leakage of tenants’ privacy policy, this paper presents a trusted third party model to manage the policy of tenants’ customized privacy preserving. The experiment certified it’s an effective and practical privacy preserving mechanism.

In Pervasive Computing Environments (PCE), existing Context-Aware Access Control (CAAC) models mainly extend the RBAC model to realize the context awareness and take into account the uncertainty of the imperfect context information by excessive constraints of the QoC (Quality of Context) parameters or degrees. To solve the problems, we present a novel QoC-Aware Access Control (QAAC) model which applies fuzzy inference to make authorization decisions. The QoC-awareness is reflected in the modification of the provided context and the fuzzy inference process. Compared with existing work, the proposed model has a more comprehensive utilization of static and dynamic attributes, better adaption to the context dynamicity, feasibility in QoC-awareness and semantic expressiveness.

Flash memory based Solid State Drives(SSDs) become an indispensable part in mobile computers. To protect confidential data from being leaked, user have to run secure deletion software to erase the confidential files. However the traditional secure deletion software may report success on SSDs, but do not work at all. To solve the problem, we proposed a per-file secure deletion method to clean up the sensitive data without erase the whole SSD. In addition, RAID technique is also employed to enhance the reliability and eliminate the potential risk caused by secure deletion.

Message security in multi-hop infrastructure-less networks such as Mobile Ad Hoc Networks has proven to still be a challenging task. A number of trust-based secure routing protocols have recently been introduced which comprise the traditional route discovery phase and a data transmission phase. In the later, the action of relaying the data from one mobile node to another relies on the peculiarity of the wireless transmission medium as well as the capability of source nodes to keep their energy level at an acceptable and reasonable level, posing another concern which is that of energy efficiency. This paper proposes an Energy-aware Trust Based Multi-path secured routing scheme (E-TBM) for MANETs, based on the dynamic routing protocol. Results show that our E-TBM scheme outperforms the Trust Based Multi-path (TBM) secured routing scheme - chosen as benchmark - in terms of energy consumption in the selected routing paths, and number of dead nodes, chosen as performance metrics.

Location-Based Services (LBSs) are becoming popular due to the advances in wireless networks and positioning capabilities. Providing user’s exact location to the LBS server may lead revealing his private information to unauthorized parties (e.g., adversaries). There exist two main fields of research to overcome this problem. They are cloaking region based query processing methods which blur a user’s location into a cloaking region and Private Information Retrieval (PIR) based query processing methods which encrypt location data by using PIR protocol. However, the main disadvantages of existing work are high computation and communication overheads. To resolve these problems, we propose a grid-based approximate k-NN query processing algorithm by combining above two methods. Through performance analysis, we have shown that our scheme outperforms the existing work in terms of both query processing time and accuracy of the result set.

Due to the explosive growth of location-detection devices, such as GPS (Global Positioning System), a user’ privacy threat is continuously increasing in location-based services (LBSs). However, the user must precisely disclose his/her exact location to the LBS while using such services. So, it is a key challenge to efficiently preserve a user’s privacy in LBSs. For this, the existing method employs a 2PASS cloaking framework that not only hides the actual user location but also reduces bandwidth consumption. However, it suffers from privacy attack. Therefore, we, in this paper, propose a density-based k-anonymization scheme using a weighted adjacency graph to preserve a user’s privacy. Our k-anonymization scheme can reduce bandwidth usages and efficiently support k-nearest neighbor queries without revealing the private information of the query initiator. We demonstrate from experimental results that our scheme yields much better performance than the existing one.

In recent years, wireless sensor networks are widely used in many areas. Collecting information efficiently and deliver to base station reliably among the hot topics in wireless sensor networks. Most of the previous studies used the Geographic routing to resolve this problem. Sensors have to know not only their location information, but also one hop neighbor and destination location information. Generally, the Global Positioning System (GPS) provides location and time information, but it will increase the cost, power consumption, and reduce the lifetime of wireless sensor network. In this paper, we propose a Virtual Coordinate System (VCS). With the VCS, WSNs can find the four extreme nodes in the scene as virtual anchor nodes. Then, a shortest path between virtual anchor nodes and sink for transfer data in the random distribution network is created. In this approach, establish a low-power, extend the network lifetime, efficient and fault-tolerant routing mechanism.

This paper assesses the performance of a tour scheduling and recommender service for electric vehicles, aiming at verifying its effectiveness and practicality as a real-life application. The tour service, targeting at electric vehicles suffering from short driving range, generates a time-efficient tour and charging schedule. It combines two computing models, one for user-specified essential tour spots as the traveling salesman problem and the other for service-recommended optional spots as the orienteering problem. As it is designed based on genetic algorithms, this paper intensively measures the effect of the population size and the number of iterations to waiting time, tour length, and the number of visitable spots included in the final schedule. The experiment result, obtained through a prototype implementations, shows that our scheme can stably find an efficient tour schedule having a converged fitness value both on average and overloaded set of user selection.

The worldwide markets for Machine-to-machine (M2M) communications over cellular networks are expected to grow for the time being. However, since the M2M communications has the characteristics that are quite different from existing human-centered wireless communications, it poses significant challe. In this paper, we address the challenges in facilitating M2M call admission and scheduling over LTE-A networks and propose a call admission method that improves the call drop probability. Such improment is made possible by adjusting the maximum number of the QoS classes. The simulation results show that the proposed method is superior to other fixed QoS class schemes in terms of the call drop probability.

Route recovery process of Ad-hoc On-demand Distance Vector (AODV) protocol has been extensively studied. However, the recovery process still requires long delays and overheads. In this paper, an enhanced method to perform quick local recovery process is proposed. In the proposed method, when a link is broken, a node detecting a link-break asks to neighbor nodes who can be a substitute for a node causing the link– break. If there is such a node, then the recovery is quickly and locally completed. The proposed method does not increase overhead to find the substitute comparing to the conventional AODV protocol. This paper provides only the idea at this time, but the performance evaluations for the proposed method will be provided in the upcoming works.

Monitoring information on the behavior of dementia patients could improve their health and safety, and thus quality of life. To monitor daily activities, dementia patients require portable and wearable monitoring device. Various sensor technologies are currently used to monitor emergency situations such as falling down and wandering activities as a result of memory and cognitive impairment. Therefore, in this research paper, a watch-type device (Smart Watch), server system, and step detection algorithm utilizing a 3-axis acceleration sensor are developed. The suggested step detection algorithm showed an accuracy of 96% in verifying normal steps.

Recently there has been much research on fulfilling tasks such as surveillance and reconnaissance coupled with a sensor networks system. It is possible to realize the system because of many technical progresses in the area of sensor networks such as signal processing, wireless networks, sensor deployment, etc. To construct sensor network systems effectively and efficiently, lots of considerations such as user requirements, sensor capabilities, and signal processing technologies should be reviewed. Consistent and unambiguous architecture for the development process coupled with the technologies should be built. This paper presents a verifiable logical architecture with petri net.

U-Home is a home-service through an interaction between human and object. Smart-home-middle-wear provides its users with services needed through interactions between users and home equipment. In this study, users’ conditions in four rooms with Smart-home-middle-wear using had been sent through EG sensor device and they were then classified by emotion-perceiving-agent-system adapting an algorithm. The emotions, which were experimented, had been divided into eight categories; Normal, Happy, Surprise, Fear, Neural, Joy, Stress(Yes) and Stress(No). In this study’s experiments, modified Decision Tree algorithm was adapted and it extracted over 90% of results totally.

To meet increasing smart device services, wireless networks have smaller cellular architecture compared to previous that. Nevertheless, future communication systems will need more communication channel capacity than current one. The systems will have the problems that they cannot be avoid the concentrated bottleneck by monotonous communication path through base station or mobile switching center.

To overcome these bottleneck problems, we propose a new dynamic cellular architecture called DNA with

dynamic cell

, which can be created or deleted by service servers or mobile hosts. Thus, the DNA architecture can support various communication channels among base stations and smart devices. Also, the proposed architecture saves channel capacity for accepting more mobile hosts.

In this paper, we model the multilevel statistical structure as Hierarchical Hidden Markov Models (HHMM) for the problem of predicting the state of human behavior based on user profile in a ubiquitous home network. Algorithms to analyze the behavioral patterns of a user using the information provided by the user in a home network system. We propose the detecting of abnormal behavior algorithm, which builds profile based on the actions taken when the user enters a room. The main contributions of this paper lie in the application of the shared structure HHMM, the estimation of the state of a user’s behavior, and the detection of abnormal behavior. The user behavior data from an experiment show that directly modeling shared structures improves the recognition efficiency and prediction accuracy for the state of a human’s behavior when compared with a flat HMM.

Realistic shading models can be synthesized in real-time game play environments in which seamless scenes are able to be simulated by reflecting light transport through layered material. In this paper, we have proposed an advanced facial skin rendering as conveying actual Fresnel refractive indices derived from actually measured data on a real human face. The Fresnel index is contingent on the location on a face because facial tissue components are slightly different. To realize physically-based rendering, we have employed a hybrid shading technique that can be merged from both improved Oren-Nayar and layered Phong model. We have shown experimental results to verify the proposed method as well.

Recently, there is an increasing interest in and research on human engineering and emotion engineering. As a basic research on biofeedback interface technology, the development of a system for processing and modeling complex biomedical signals is very important, and these technologies will eventually offer a pleasant life environment, so the human-centered system based on biomedical signal analysis is the keyword of the future technology. In this study, a biofeedback interface was designed to analyze biomedical signals (EEG, ECG) to recognize the user concentration and emotion state as well as effectively assessing the user intention. Compared with the existing interface technique using single biomedical signals, the proposed technology can analyze complex biomedical signals to make it easy to assess the user state and intention and enhance the utilization thereof.

In this paper, we proposed Reduced Whole Acknowledgement (RWA) method which was based on Multiple Acknowledgement (MA) [1] method and proposed by Smart Block Medium Access Control (SBMAC) [2]. The proposed method can reply the information of transmission error states of all Senders within smaller storage space. Especially, the number of transmission and the frame length was minimized to reduce transmission error. The performance of the proposed method and conventional methods such as Normal Multiple Acknowledgement (NMA) and Selective Multiple Acknowledgement (SMA) method [3] was calculated and compared with each other. The calculation results showed the best performance in case of the proposed method .

Many steganography schemes were invented for the purpose of safe communication. Such previous schemes often show good and reasonable performance, however, few have been based on paletted images; it is not easy to invent good steganographic schemes with little evidence of data hiding. In this paper, we propose new hiding schemes (

r

,

N

,

k

) based on binary images. The proposed hiding scheme (

r

,

N

,

k

) applied to paletted images using the Optimal Parity Assignment (OPA) approach. Experimental results show that the proposed palette-scheme (3,18,9) exhibits good performance compared to that of previous schemes.

The most of very large system by growing the variety of applications, the relationships between the requirements and the program components are more complex. A single requirement may be implemented by a number of components and each component may include elements of several requirements. Moreover, these requirements become critical when considering conceptual model by smart applications and smart platform, which are capable of optimizing their behavior or context of execution depending on themselves. Accordingly, we propose to aspect oriented software engineering in our adaptive smart vehicle middleware platform to influence the development and the concern OSGi oriented requirement in this paper.

We present our study on the optimal mortgage refinancing problem under a stochastic interest rate environment. Through Monte Carlo simulations we try to identify the optimal time for refinancing such that the overall cost is minimised. Experimental results reveal that such a time is more likely to appear at the early stage of a mortgage contract. Through simulations we also generate time-dependent threshold rates for optimal refinancing. At a particular time, if market interest rate falls below such a threshold refinancing is most likely to be optimal. To accelerate the generation of the threshold rates we developed a multi-threaded program, which demonstrated more than three-time speedups against an efficiently-written sequential program on a quad-core Intel Corei7 2600 in all the test cases.

We present out work on computing the prices of American call and put options and the values of their Greek letters. The underlying stocks of the options are assumed to pay out cash dividends. For calculating option prices and their Greek letters we use the Leisen-Reimer binomial method. Through experiments we demonstrate that it converges both faster and more smoothly than the Cox-Ross-Rubinstein binomial method. We also present plots for the Greek letters calculated from American call and put options on non-dividend paying stocks. The calculation of the Greek letters with the Leisen-Reimer binomial method is explained.

The strategic application domains of Cyber Physical Systems (CPS) [7,6] include health care, transportation, managing large-scale physical infrastructures, and defense systems (avionics). In all these applications there is a need to acquire reliable resources in order to provide trustworthy services at every service request context. Hence we view CPS as a large distributed highway for services and supply chain management. In traditional service-oriented systems service, but not resource, is a first class entity in the architecture model and resources are assumed to be available at run time to provide services. However resource quality and availability are determining factors for timeliness and trustworthiness of CPS services, especially during emergencies. So in the service-oriented view of CPS discussed in this paper we place services around resources, because resource constrain service quality. We investigate a

resource-centric

, and

context-dependent

model for

service-oriented

CPS and discuss

3-tiered

architecture for

service-oriented

CPS in this paper.

This paper studies the implied volatilities of the S &P 100 from the prices of the American put options written on the same index. The computations are based on a recursive Binomial algorithm with prescribed error tolerance. The results show that the volatility smile exists, thus the classic Black-Scholes’s approach of using a constant volatility for pricing options with different trading conditions is not plausible. The method discussed in this work contrasts the likelihood ratio method contained in [6]. Further studies with expanded data set are recommended for comparing the effectiveness of these two methods in forecasting stock market shocks.

Wireless capsule endoscopy (WCE) is an ingestible electronic diagnostic device capable of working wirelessly, without all the limitations of traditional wired diagnosing tools, such as cable discomfort and the inability to examine highly convoluted sections of the small intestine. However, this technique is still encountering a lot of practical challenges and requires further improvements. This paper is to propose the methodology of investigating the performance of a WCE system by studying its electromagnetic (EM) wave propagation through the human body. Based on this investigation, the capsule’s positioning information can be obtained. The WCE transmission channel model is constructed to evaluate signal attenuations and to determine capsule position. The detail of this proposed research methodology is presented in this paper.

Contemporary technical experimentations become complicated. Therefore, a smart laboratory environment is needed for effective laboratory activities. In particular, a monitoring/surveillance system is needed to detect and regulate extreme ambient conditions in the laboratory. In this paper, we describe how a thermal comfort laboratory surveillance system is constructed via the deployment of a wireless sensor network (WSN). In order to prolong system lifetime as well as improve system reliability, a habit-based adaptive sensing mechanism has been proposed. Evaluations of on-site deployment results indicate the functionality and feasibility of the proposed WSN.

Many problems facing software engineers demand ‘optimal’ performance in multiple dimensions, such as computational overhead and development overhead. For these complex problems, designing an optimal solution based upon a single programming paradigm is not feasible. A more appropriate solution is to create a solution framework that embraces multiple programming paradigms, each of which is optimal for a well-defined region of the problem space. This paper proposes a theory for creating multi-paradigm software solutions that is inspired by two contributions from theoretical physics: model dependent realism and M-Theory. The proposed theoretical framework, which we call ‘S-Theory’, promotes the creation of actor-optimal solution frameworks, encourages technology reuse and identifies promising research directions. We use the field of sensor networks as a running example.

The IVEF service is the draft standard designed for exchange of information on sea traffic between the vessel traffic systems and between the vessels. Standardization of this service is under way as a part of the next-generation navigation system, called e-Navigation. The International Association of Lighthouse Authorities (IALA) suggests, on its recommendation V-145, the IVEF service model and the protocol for provisioning of this service. But the detailed configuration of this service must be designed by the users. This paper suggests, based on the basic service model and protocol provided in the recommendation V-145, the design of the J-VTS middleware which will facilitate exchange of information on sea traffic.

This paper is concerned with the security of a three-party password-authenticated key exchange protocol presented by Abdalla and Pointcheval in FC’05. Abdalla and Pointcheval’s protocol makes use of a hash function

F

whose outputs are elements of a cyclic group G of prime order. Such a hash function

F

can be constructed from a typical hash function in various ways. In this paper, we consider the case that

F

(.) =

g

h

(.)

, where

g

is an arbitrary generator of G and

h

is a hash function such as SHA-1 and MD5. Our result is that such a construction of

F

immediately leads to the vulnerability of the Abdalla-Pointcheval protocol to an off-line dictionary attack. We also show how to address this weakness of the protocol.

The technique of classification can sort data into various categories for data mining studies. The demand for sequence data classification has increased with the development of information technology. Several applications involve decision prediction based on sequence data, but the traditional classification methods are unsuitable for sequence data. Thus, this paper proposes a Pattern Coverage Rate-based Sequence Classification Model (PCRSCM) to integrate sequential pattern mining and classification techniques. PCRSCM mines sequential patterns to find characteristics of each class, and then calculates pattern coverage rates and class scores to predict the class of a sequence. The experimental results show that PCRSCM exhibits excellent prediction performance on synthetic and real sequence data.

The 7th National Curriculum includes the courses on electronic goods (Practical Course) and roles of robot in the future (Social Studies), which are not sufficient for students to learn about characteristics and functions of robots. As a complementary measure, in order to enhance logical thinking of students through programming of movement of robots, robot education programs have been suggested and are under development. This study suggests the programmable line tracer robot course which provides the elementary school students with the experience of producing and controlling robots. This study also suggests the convergence robot education program to be developed link with the regular curriculum, and analyzes the method of teaching based on the teaching plans.

Recently Chang, Lee, and Chiu proposed an enhanced authentication scheme with anonymity for roaming service in global mobility networks. Their scheme is suitable for mobile environments. This is because it uses only low-cost functions such as one-way hash functions and exclusive-OR operations. After that, Youn, Park, and Lim showed the weaknesses of Chang et al.’s scheme without any countermeasures. In this paper, we propose an improved authentication scheme with anonymity by basing on low-cost functions as Chang et al.’s scheme. The proposed scheme overcomes the security flaws demonstrated by Youn et al. by adopting two secret values and a virtual identity. Therefore, our scheme is more secure and still efficient when compared with Chang et al.’s scheme.

In 2012, Sun et al. proposed an authenticated group key transfer protocol based on secret sharing instead of encryption algorithm. They claimed that their protocol provides mutual authentication to ensure that only the authorized group members can recover the right session key and all participants only need to store one secret share for all sessions. However, our analysis shows that Sun et al.’s protocol is vulnerable to outsider and insider attacks and does not provide mutual authentication. In this paper, we show a detailed analysis of flaws in Sun et al.’s protocol.

Indiscreet distribution of harmful content, excessive exposure to violent material and excessive use of the Internet are becoming an axis of social conflicts, and the damage is expanding to lower ages. At the introduction of media, we were in great expectation on its educational use. It has become, however, the most harmful environment from the aspect of education. Media education can be in two aspects: education to accept, product and utilize media to activate the positive functions; and protective and preventive education to minimize the negative functions. What is worthy of note is that media education can be carried out in the aspects of both the positive functions and the negative functions of media. This study suggests the media education program applicable to elementary schools, noting the aspects of both the positive functions and the negative functions of media.

This paper is about access control of illegal and objectionable contents for child online protection coming through the combination of smart phone device, as the core technology of ubiquitous environments. To overcome the shortcoming of simple access control of illegal and objectionable contents on current internet, we suggest a framework for content-based classification and propose an access control of illegal and objectionable content’s framework architecture using it. This paper suggests a solution to block the access of the illegal harmful contents by classifying the contents in detail instead of the existing simple user age classes for the multimedia contents.

Current smart grid service protocol is not defined as a standard but is only material items for security procedures, message, and policies. In other words, this has no contents on the standards of elucidating delivery security for network safety and data perfection or any standards or requirements on the security for a safe information exchange. Therefore, sensitive information between nations needs to consider many different factors, which may require a complex security structure. Therefore, this paper suggests a security structure that can automatically be connected based on characteristics while sending security policy and security request messages when the smart grid users desire a connection with standard service protocol.

Security vulnerabilities exist in end point devices such as PDA’s, laptops, Blackberries, tablets, etc. Examples of endpoint software include anti spyware / malware software, encryption software, Data Loss Prevention system, Security USB and Device Control S/W, client operating system based firewalls, etc. It is important to note that leveraging company security policy and ensuring that it is enforced through stringent monitoring of in-house security breaches, further enhance the effectiveness of end point security. However, no criteria have been established as yet to evaluate whether such End point Security Software correctly provides the basic security functions needed by user and whether such functions have been securely developed. Therefore, this paper proposes security requirements of End point Security Software by modeling a threat and applying a security requirement engineering methodology based on Common Criteria.

Recently, Phishing is a significant security threat to users and has been easy and effective way for trickery and deception on the internet. Phishing is an attempt to acquire our information as well as financial information without user’s knowledge by making similar kind of website or sending e-mails to users. Some of the widely available and used phishing detection techniques include whitelisting, blacklisting, and heuristics. But, absolute and perfect anti-phishing solutions and techniques are hard to fine due to a variability of phishing site domain. This paper aims to collect and filter out phishing suspicious URLs before determine phishing sites using Spamtrap system which is a honeypot used to collect spam e-mail. Spam e-mail usually contain phishing site URLs, so we can collect phishing site URLs from spam e-mail of spamtrap system. After collect URLs that can be phishing sites, many kind of phishing site detection algorithm can be used in our paper.

In 2009, Tseng et al. proposed a key agreement protocol based on chaotic maps. Tseng et al. claimed that their protocol preserve user anonymity. However, Tseng et al.’s protocol is insecure against the insider attack. Nui et al. proposed a new anonymous key agreement protocol in 2011. Unfortunately, Nui et al.’s protocol cannot provide user anonymity and has computational efficiency problem. We introduce a new key agreement protocol based on Chebyshev chaotic map. Our protocol overcomes these security problems and provides user anonymity.

The QoS performance of wireless mesh networks (WMNs) is measured by the topology connectivity as well as the client coverage, both of which are related to the problem of router nodes placement, in which each mesh client is served as equal. In practice, however, mesh clients with different payments for the network services should be provided by different qualities of network connectivity and QoS. As a result, to respond to the practical requirement, this paper considers the router nodes placement problem in WMNs with service priority constraint in which each mesh client is additionally associated with a service priority value, and we constrain that the mesh clients with the top one-third priority values must be served. Our concerned problem inherited from the original problem is computationally intractable in general, and hence this paper further proposes a novel simulated annealing (SA) approach that adds momentum terms to search resolutions more effectively. Momentum terms can be used to improve speed and accuracy of the original annealing schedulers, and to prevent extreme changes in values of acceptance probability function. Finally, this paper simulates the proposed novel SA approach for different-size instances, and discusses the effect of different parameters and annealing schedulers.

For networksurvivability, recovery methods from link or node failures should be provided and spare capacity to perform recovery should be prepared on the network links. The efficiency of spare capacity provisioning is a key issue in survivable network design. In this paper, we studied topology information based capacity provisioning methods for WDM optical networks which are widly used as a backbone architecture of current Internet.In the methods, the spare wavelengths are reserved to perform optical link protection using only topology information of a network without need to calculate the amount of on-going traffic of the network, thus provide simple and efficient spapre capacity planning. The basic idea of the topology information based methods is embedding virtual cycles to perform recovery on the network topology graphs.We suggest a multiple ring-cover based spare capacity provisioning scheme and compare it with two other topology information based schemes called cyclic-double-cover and p-cycle. We provide performance analysis of the topology information based schemes by the numerical calculation using cut-sets of the topology graphs, and compare it with computer simulation results.

Generally, it is known that only quality-assuring services can provide a reasonable profit model. However until now a practical profit model considering the service cost and quality simultaneously has not been introduced yet. Recently, the Quality of Experience (QoE) was suggested to measure user’s real satisfaction level. The QoE is expected to be used for efficient service provisioning and criteria for accurate satisfaction measuring. This paper introduces a profit model for the contents providers considering the costs for quality services and the QoE together. Especially, we assume that the QoE with user’s feedback can be interpreted as the intention to pay for the services. We take into account that QoE is dependent on service area, demographic information and user group characteristics. The proposed profit model can be used for contents providers to find an optimum investment which maximizes the profit.

Self-adaptive software is an essential approach to manage the challenges of establishing system that autonomously responds to a variety of context-aware situation. In addition, self-adaptive software use a lot of policies and explicitly or implicitly between rules and cases to decide how to react to monitored events. For theses, Self-adaptive systems persistingly develop and modify behavioral properties to meet changing demands. Most of important, specification of adaptation policy is based on element in the construction of architecture-based hybrid model. However, several rules are usually scattered in different procedures, which makes procedures more complex, as well as cases are merely recognized situation by the rule and case. Accordingly, in this paper, we presents what is hybrid model including architecture-centric semantic schema. Also, a core element in architectural self-adaptive systems is the specification of adaptation policy: the mapping between hybrid observer indicating the need for an adaptation and hybrid diagnosis of properties with regulator in this need, along with an expression of self-adaptive schema algorithm.

The optimal channel sensing problem in cognitive radio networks with multiple secondary users sharing a channel with primary users based on channel sensing is considered. Based on the previous system model and results in [1], we extend to cases with multiple secondary users. The characteristics of a sum rate and the optimal sensing are investigated. It is shown that the optimal sensing point is determined depending on the primary activity factor, primary and secondary link qualities.

This paper presents a QoS-guaranteed transmission of H.264 video over Wireless Mesh Networks (WMNs) based on an adaptive cross-layer mapping of IEEE 802.11e MAC strategy. We call this MDCA (Mesh Distributed Channel Access) MAC strategy as it is based on 802.11e standard with adaptive mechanism in response to dynamic nature of mesh networks. This novel MDCA strategy employs the channel reservation control packets at the MAC layer to exchange timely Channel State Estimation information for an optimal FEC at the application layer as well as the QoS-centric GEDSR model [1] for an optimal adaptation. The proposed scheme offers an optimized transmission to guarantee the minimum packets delay and drop rate needed for video over WMNs. In this research, we resolve the problem associated with 802.11e standard by designing an integrated scheme that allows the system to achieve the optimal transmission via a FEC implemented in the application layer. We evaluate the proposed scheme based on network-level metrics, including bit rate, packets delay and drop rates in comparison with the static cross-layer mapping scheme based on 802.11e WMNs. We can confirm that the adaptive cross-layer mapping strategy MDCA outperforms the static cross-layer mapping scheme by a significant margin.

In this paper, a combined OFDM system and bandpass sampling method using Multiple Signal Classification(MUSIC) algorithm for automatic (angle of arrival) AOA tracking is discussed. And we propose a new method that adding (time division multiplexing)TDM with bandpass sampling in the same time to avoid interference due to RF filter characteristics. Also, we consider Doppler effect for the targets’ movement and after compensating the Doppler effect with a valid range , the system performances well. Computer simulation shows that the performances of MUSIC spectrum for AOA due to various conditions and demonstrates the accuracy of AOA estimations.

The BYOD (Bring Your Own Device) based mobile office services become popular as the rapid growth of smartphone users. However, malicious codes are also widespread, therefore security threats become serious problems. This paper suggests WLSA (White-List based Security Architecture) for the better mobile office security and presents required procedures and the analysis of the expected security enhancement.

Recently, the marine accidents happened due to the ship deviation from the established route or seaway. Due to the sensitivity of the problem, the Automatic Identification System (AIS) has been studied to improve the safety in seaway traffic. In this paper, we propose the seaway deviation prevention scheme that makes use of the distance of ship from a seaway based on a triangulation method for preventing ship collision. This scheme devises a control strategy for ships which keeps the ship in the route range and prevents the ship deviation from the normal sea route with a route range. This scheme could be used to prevent marine accidents and increase the ship’s safety degree.

In this paper, we analyze the energy consumption of edge router with sleep mode in OBS networks. The edge router with sleep mode consists of multiple line cards, multiple OBS line cards, a SCU(Switch Control Unit) and an electronic switch fabric. The OBS line card, which is the main part of edge router, performs the functions of edge router such as BCP(Burst Control Packet) and burst assembly, BCP scheduling and sleep mode. In OBS line card, it is possible to reduce energy consumption by controlling PHY/Transceiver module from active state to sleep state for burst assembling by using sleep mode. In order to evaluate the energy saving performance of the OBS edge router with sleep mode, the power consumption is analyzed according to the datasheet of packet router and optical device. And, simulation by using OPNET is also performed in terms of sleep time and average queuing delay.

In this paper, we propose a multi-hop transmission system using visible light communication to transmit audio data. In our proposed transmission system, at the transmitter we encode audio data based on S/PDIF standard – a popular standard for digital audio signal, and transmit the encoded audio signal via general LED. At each relay, digital audio signal is improved and amplified before sending. At the receiver, encoded audio signal from photodiode (PD) is decoded, amplified and coverted to analog audio signal. We evaluate our proposed transmission system in a room with flourescent light source. The audio signals obversed at the receiver show that with the support of relays, our proposed transmission system can provide high quality audio transmission from transmiter to receiver via multi-hop relays at a long distance.

The performance of mobile ad-hoc wireless networks is highly sensitive to node-to-node connection caused by node movement. Thus, to create robust mobile ad-hoc networks against node mobility, stable routing paths and routing refresh interval should be selected adaptively based on instantaneous network parameters. In this paper, we present a practical adaptive scheme to improve network stability in mobile ad-hoc networks by adaptively selecting most stable routing paths and optimal routing refresh interval. We validate our proposed adaptive scheme via simulation using OPNET. The simulation results in different scenarios demonstrate our proposed scheme remarkably enhances the network stability, providing robust mobile ad-hoc wireless networks.

Geomulticast is a specialized location-dependent multicasting technique, where messages are multicasted to some specific user groups within a specific area [1]. In this paper, we propose a routing protocol for supporting geomulticast service based on route stability in mobile ad-hoc wireless networks. The main features and contributions of the proposed method are as follows. First, we present a direction guided routing method that can reduce control overhead for construction of routes and improve data transmission efficiency. Second, we introduce how to calculate and evaluate link stability between two nodes as well as route stability of multi-hop quantitatively by using nodes’ mobility. Third, we can establish the most stable path by using those two information, link stability and route stability, between a source node and a representative node as well as a representative node and candidate destination nodes within some specific region in order to deliver packets with reliability, reduced overhead, and improved data transmission efficiency. Fourth, a route stability model is presented. We evaluate the proposed routing protocol by using OPNET. The results show that the proposed routing can support the geomulticast services effectively in mobile ad-hoc wireless networks.

Disasters such as fires, earthquakes, and acts of terror in public places such as subway stations, airports, and department stores can lead to tragic consequences. Although a number of studies are being conducted on indoor location recognition systems, they are not appropriate for emergency rescue evacuation support system (ERESS), which requires building new infrastructures in the indoor environment of all public buildings. This paper proposes an RFID-based indoor location recognition system for the ERESS. The proposed indoor location recognition system uses RFID readers and active tags to collect position coordinates in real time, allowing a single tag to monitor actual locations. Performance evaluation based on experiments indicates that the proposed indoor location recognition system is effective for monitoring indoor pedestrians in ERESS applications.

Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing lifetime of wireless sensor networks. In this paper, we present the symmetric hierarchical clustering strategy related to sink position and energy threshold in wireless sensor networks. This protocol allows networks topology to be adaptive to the change of the sink position by using symmetrical clustering that restricts the growth of clusters based on depth of the tree. In addition, it also guarantees each cluster has the equal lifetime, which may be extended compared with the existing clustering protocols. We evaluated the performance of our clustering scheme comparing to existing protocols, and our protocol is observed to outperform existing protocols in terms of energy consumption and longevity of the network.

Recently, fire accidents in large buildings usually cause in tragic consequences. Many buildings are currently equipped with modern fire detection systems for preventing such accidents, but these support no clues as to how to escape. A lot of evacuation systems are aiming at providing more efficient means for alarming and guiding people. The evacuee guidance simulator provides to give clear navigation to nearest exit. This simulator must generate virtual objects such as sensors and guidance lights, connects it with nodes, inputs necessary information, and sets up virtual building environments. In this paper, we present the architecture for creating virtual objects to develop an evacuation guidance simulator. This simulator supports to evacuate people from the disaster area or the outbreak of fire with rapidity and safety for the virtual condition that a disaster or fire occurs in a large scale building.

In this study, we present an efficient finite field arithmetic algorithm for multiplication which is a core algorithm for division and exponentiation operations. In order to obtain a dedicated pipelined algorithm, we adopt Montgomery algorithm and cellular systolic array. First of all, we select an effective Montgomery factor for the design of our parallel algorithm, then we induce an efficient multiplication algorithm from the typical binary MM algorithm using the factor. In this paper, we show the detail derivation process in order to obtain the recursive equations for pipelined computation.

Through ‘Twitter’, one of the Social Network Service, people can have relationships by using ‘Follow’, a function of Twitter. Every user has different purposes, so there are various ‘Followers’, These Followers follow somebody in favor of them or just to support them without reasons or to criticize or watch one’s behavior or tweet(one’s comments). In this paper, a Model is suggested that why they follow certain users by using network relations between followers. User’s influential supporters and influential non-supporters are extracted and then supporters, neutrals, and non-supporters are classified by follower’s retweet information, profile and recent tweet sentiment analysis. In order to verify this suggestion’s validity, random 30,000 users who follow one of the 5 politicians are extracted to experiment. After the experiment, I got to know that supports from influential support-followers and influential nonsupport- followers and non-support-followers classification was effective.

In this paper, we proposed an initial quantization parameter (

QP

) decision method based on frame complexity with multiple objectives of

GOP

(Group of Pictures) for H.264 rate control algorithm. Primarily, we choose four video sequences with different characteristics to constitute a sample space and find their optimal

initial QP

s which can guarantee to generate video sequences with consistent quality by minimizing the variation of

QP

s in a

GOP

, while ensuring the minimizing actual encoding bit rate closer to the target bit rate in various bit rates. And then we calculate the spatial characteristic of tested video sequences using the proportion of the number of complex MBs in the first I-frame. The optimal

initial QP

s are represented in a two-dimensional matrix form arranged in spatial characteristic and target bit rate according to proposed selection method of optimal

initial QP

. When any video sequence is given under any target bit rate, its spatial characteristic is calculated and mapped to one of four samples through the proposed mapping method. Finally, its optimal

initial QP

is determined by picking an element of matrix according to the mapped spatial characteristic and given target bit rate. Simulation results show that the proposed method achieves more obvious consistency in objective

PSNR

s and has secured encoding bit rate than noted algorithms.

We developed an encryption system using an AES encoding algorithm for the Internet telephone system security to prevent eavesdropping. It works through tapping by encoding/decoding the output data of the Internet telephone on the sending and receiving sides when the caller or callee is making an internet phone call. The developed encryption system has the merit of no deterioration of voice data not related to the encoding process. The privacy telephone set against eavesdropping was designed to prevent eavesdropping on internet telephones during communication and involved encoding/decoding the output data at the transmitter and receiver of internet telephones.

In 2012, Singh-Verma proposed an ID-based proxy signature scheme with message recovery. Unfortunately, by giving two concrete attacks, Tian et al. showed that Singh-Verma’s scheme is not secure. This paper proposes an improvement of Singh-Verma’s scheme to eliminate the security problems.

The authors of the paper “Scheduling Optimization of the RFID Tagged Explosive Storage Based on Genetic Algorithm” (Xiaoling Wu, Huawei Fu, Xiaomin He, Guangcong Liu, Jianjun Li, Hainan Chen, Qianqiu Wang, and Qing He), DOI: 10.1007/978-3-642-38027-3_38, appearing on pages 358-366 of this publication, have decided to retract the paper, because there are serious flaws in both the data and some steps of the algorithm. This makes the data unreliable.