Informatics Engineering and Information Science

Improving accuracy in time series prediction has always been a challenging task for researchers. Prediction of time series data in healthcare such as HIV/AIDS data assumes importance in healthcare management. Statistical techniques such as moving average (MA), weighted moving average (WMA) and autoregressive integrated moving average (ARIMA) models have limitations in handling the non-linear relationships among the data. Artificial intelligence (AI) techniques such as neural networks are considered to be better for prediction of non-linear data. In general, for complex healthcare data, it may be difficult to obtain high prediction accuracy rates using the statistical or AI models individually. To solve this problem, a hybrid model such as adaptive neuro-fuzzy inference system (ANFIS) is required. In this paper, we propose an improved ANFIS model to predict HIV/AIDS data. Using two statistical indicators, namely, Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), the prediction accuracy of the proposed model is compared with the accuracies obtained with MA, WMA, ARIMA and Neural Network models based on HIV/AIDS data. The results indicate that the proposed model yields improvements as high as 87.84% compared to the other models.

Wavelet Neural Network (WNN) is a method based on the combination of neural network and wavelet theories. The disadvantage of WNN is the lack of structured method to determine the optimum level of WNN factors, which are mostly set by trial and error. The factors affecting the performance of WNN are the level of MODWT decomposition, the wavelet family, the lag inputs, and the number of neurons in the hidden layer. This research presents the use of design of experiments for planning the possible combination of factor levels in order to get the best WNN. The number of tourist arrivals in Indonesia via Soekarno-Hatta airport in Jakarta and via Ngurah Rai airport in Bali is used as case study. The result shows that design of experiments is a practical approach to determine the best combination of WNN factor level. The best WNN for data in Soekarno-Hatta airport is WNN with level 4 of MODWT decomposition, Daubechies wavelet, and 1 neuron in the hidden layer. Whereas, the best WNN for data in Ngurah Rai airport is WNN with MODWT decomposition level 3 and using input proposed by Renaud, Starck, and Murtagh [11] and seasonal lag input addition.

Presently, Network security is the most concerned subject matter because with the rapid use of internet technology and further dependence on network for keeping our data secure, it’s becoming impossible to protect from vulnerable attacks. Intrusion detection systems (IDS) are the key solution for detecting these attacks so that the network remains reliable. There are different classification approaches used to implement IDS in order to increase their efficiency in terms of detection rate. Support vector machine (SVM) is used for classification in IDS due to its good generalization ability and non linear classification using different kernel functions and performs well as compared to other classifiers. Different Kernels of SVM are used for different problems to enhance performance rate. In this paper, we provide a review of the SVM and its kernel approaches in IDS for future research and implementation towards the development of optimal approach in intrusion detection system with maximum detection rate and minimized false alarms.

Wireless Sensor Networks (WSNs) are composed of many sensor nodes using limited power resources. Therefore efficient power consumption is the most important issue in such networks. One way to reduce power consumption of sensor nodes is reducing the number of wireless communication between nodes by dual prediction. In this approach, the sink node instead of direct communication, exploits a time series model to predict local readings of sensor nodes with certain accuracy. There are different linear and non-linear models for time series forecasting. In this paper we will introduce a hybrid prediction model that is created from combination of ARIMA model as linear prediction model and neural network that is a non-linear model. Then, we will present a comparison between effectiveness of our approach and previous hybrid models. Experimental results show that the proposed method can be an effective way to reduce data transmission compared with existing hybrid models and also either of the components models used individually.

Nowadays, Ecology and/or Recycling are one of very important keywords to improve our daily lives efficiently and comfortably. Some products have been not-used by owners but they have still now been available. In such a case, Resource and Knowledge Recovery are very much useful at the viewpoint of Ecology and Recycling. We have tried to demonstrate how to recover some resource of furniture in order to achieve recycling and reproducing. We have utilized social networks based on Internet to perform information sharing and exchanging. This time, our resources are currently not-used furnitures kindly provided from some company which has stored several mounts of them. By means of social network based on Internet, target resources can be found and selected into the next recycle process. And then discussion how to utilize such resources are carried out for redesign and reproduction with help of professional viewpoint. Someone, who is interesting in such resources, do redesign and reproduce new products for the sake of recycling and/or resource recovery. This paper describes a case study of recycling resource of furnitures into reproductive design as a sample of Resource and Knowledge Discovery Using Social Networks based on Internet.

The influence of software team dynamics on well-organized software development knowledge process could prevent software development organizations from suffering from the knowledge atrophy problem. To explore this, we have studied several team dynamics factors that influence the Knowledge Management Processes (KMP) in Very Small Entities (VSEs) [1]. A survey was conducted in a variety of VSEs and through statistical and qualitative content analysis for the research data, results indicate that small teams, informal team process and structure have an important influence on the level of team dynamics in the software development process.

Resource discovery is the most important challenge of Grid systems. Lately many researchers tried to improve indexing and searching methods. To this aim, there are several factors affecting improvement such as time and message complexities, scalability, dynamicity, reliability, support of different types of queries, and so on.

This paper proposes a new model for resource indexing and discovery, which reduces the time and message complexities significantly. It is based on indexing the nodes and resources in a tree schema. Peers on the leaves of the tree will be in a virtual super-peer schema. Nodes are categorized hierarchically relative to their resources, so that the domain of search narrows rapidly and queries can be replied quickly and without wasted messages.

The present paper models the fundamental problems of fluid flow using a discretely improved finite difference method on a staggered computational grid. The developed finite difference formulation is applied to well-established benchmark problems, namely, the lid-driven cavity flow, the developing laminar flow in a straight rectangular duct and the backward-facing step flow. Excellent agreements have been found for all cases. Also, this approach has successfully handled the pressure of the flow that has been long considered as one of the main problems in using the finite difference method.

Recent research shows that cognitive load has an effect on gait, especially noticeable in people with neurodegenerative disorders. Most researchers in this field employ sophisticated and expensive systems to measure the variability of gait parameters under different cognitive loads. In this paper we propose the use of smart phones and off-the-shelf wireless accelerometers to implement a light-weight and low-cost system to study the influence of cognitive load on gait. Making use of this new approach, we study the effect on gait variability derived from imposing a speed while walking in a treadmill. We also compare “phone-texting” with other common “working memory” and “motor” tasks used by researchers to study the influence of cognitive load on gait. Our approach avoids the space constraints imposed by current systems during the tests, and delivers an accuracy comparable to that of the most sophisticated systems available in the market.

Gait is another potential human biometrics to look into whenever face recognition fails in video-based systems as is the case with siblings that have similar faces. We perform analyses on 10 pairs of siblings where their faces are assumed to have similarities. Our gait features are the angular displacement trajectories of walking individuals. We apply smoothing with the Bezier polynomial in our root-finding algorithm for accurate gait cycle extraction. Then, we apply classification using two different classifiers; the linear discriminant analysis (LDA) and the

k

-nearest neighbour (

k

NN). The best average correct classification rate (CCR) is 100% with a city-block distance

k

NN classifier. Hence, it is suggested that in the case where face recognition fails, gait may be the better alternative for biometric identification.

The use of Fuzzy Expert System has highly increased in the field of medicine, to diagnosis the illness of patient pursuit. By applying the intensified fuzzy verdict mechanism the diagnosis of diabetes becomes simple for medical practitioners. The intensified fuzzy verdict mechanism consists of fuzzy inference, implication and aggregation. For the diagnosis of diabetes, knowledge are represented in the form of fuzzification to convert crisp values into fuzzy values. This mechanism, contains set of rules with fuzzy operators. Defuzzification method is adopted to convert the fuzzy values into crisp values. In this paper, intensified fuzzy verdict mechanism is proposed to complete the knowledge representation and the inference model for diabetes data. The result of the proposed methods is compared with earlier method using accuracy as metrics. This mechanism is focused on increasing the accuracy and quality of knowledge for diabetes application.

In recent times, multidimensional arrays are extensively used to handle large amount of data in scientific research, engineering, and MOLAP applications. Most of the existing data structures are static in nature and cannot grow or shrink dynamically. The Traditional Multidimensional Array (TMA) is an efficient structure in terms of accessing the element of the array by straight computation of the addressing function, but TMA is not extendible during run time. There are some extendible data structures but they have the problem of address space overflow for large number of dimensions or length of dimension. In this paper we propose a new data structure, Extendible Karnaugh Array (EKA), to represent the multidimensional data. The main idea of this scheme is to represent

n

dimensional array by a set of two dimensional extendible arrays. The scheme can be extended in any direction during run time. We evaluate our proposed scheme by comparing for different operations with the Traditional Multidimensional Array (TMA). Our experimental result shows that the EKA scheme outperforms TMA.

It is important for almost all users to know how their network environment can work correctly or suitably. Especially, it is considered to be significant whether really-provided (i.e. measured) performance is similar to theoretical one based on formulation or not. Sometimes the former performance may be rather different from the latter one from a viewpoint of our experience. We have utilized a kind of video transmission system which can be used as a network conference system. Not only because such a system becomes more and more useful in the distributed campus network environment, but also because the system must transmit certain amount of packet flows between and/or among its elements while it works. Such a video transmission system may be adequate and applicable to realize effective measurement of packet flow amount in the distributed campus network as a relatively wide experimental environment. This paper describes how to configure network conference scheme in order to formulate network performance and how to measure packet flow amount at specific points in the relevant network. A trial evaluation of network performance has been also carried out through comparison of packet flow amount for formulated (i.e theoretical) network performance and really measured one.

The competency evaluation of an ontology is a semantic analysis typically performed by an ontology engineer using a premeditated set of competency questions with the aid of evaluation tool such as the Competency Question based Conceptual-Relationship Tracer (CQ-CRT). A main limitation of the CQ-CRT that has been developed as a front-end application for the Protégé editor is that its result is represented in textual form, which is sometimes long winded and bogged with unwanted redundancies. It makes the result hard to trace and difficult to understand. We intend to assist the production of a visual representation of the textual result generated by the CQCRT in order to better promote the transparency and traceability of the analytic information. Jambalaya has been identified as a suitable visualiser plugin that can be adapted for providing the visualisation support. Consequently, this paper discusses the approach we have taken to adapt and integrate Jambalaya into CQ-CRT. A systematic testing and analysis was conducted to evaluate and improve the effective functioning of the integrated CQ-CRT visualisation tool. The analysis shows that the tool is able to afford the level of interactivity and visual expressiveness that meets the desired query requirements.

Migration requires metadata about old hardware/software configurations or old computer technologies. However, current metadata schemas used in preservation systems are different and it is difficult to judge the actual quality requirement of metadata migration. This paper presents a set of quality requirements for migration metadata and the necessity and sufficiency of these requirements are evaluated with a questionnaire that was distributed internationally and followed up by several telephone interviews. The survey results indicate that our requirements are complete and can be classified into three levels, namely essentiality, necessity, and conditionality. The proposed quality requirements can be used by custodians as a checklist to examine their metadata schemas in terms of how well they can support migration.

Workflow Management Systems (

WfMS

s) are complex software systems that require proper support in terms of

WfMS

performance. We propose here an approach to obtain some performance measurements for

WfMS

s (in order to compare them) by adopting a

black box

approach – an aspect that is not yet adequately studied in literature – and report some preliminary results: this allows us to evaluate at run-time the overall performance of a

WfMS

, comprising all of its constituent elements.

We set up two reference processes and four different experiments, to simulate real circumstances of load, ranging from one process instance to several process instances, entering the system either gradually or simultaneously. We identify some key performance indicators (

CPU

, main memory and disk workloads, and completion time) for the tests. We choose five

WfMS

s (some publicly available, some commercially available), and install them in their respective default configuration on five different and separate virtual machines (

VMware

). For every

WfMS

and for every experiment, we perform measurements and specifically focus on the completion time. Results enable us to measure how efficient the

WfMS

s are in general and how well they react to an increase of workload.

In this paper, the explicit Accelerated Runge-Kutta Nyström (ARKN) method of order three with two stages for the numerical integration of second-order ordinary differential equations are developed. The method is two step in nature. Algebraic order conditions of the method are obtained and third order ARKN method is derived. Numerical examples are carried out to illustrate the efficiency of the proposed method compared to the existing Runge-Kutta Nyström (RKN) method.

In this paper, a new fuzzy model is presented to improve methods for Shariah-compliant portfolio optimization, and provides an overview of faithcompliant portfolio optimization. The spread of fuzzy variable is adopted as criteria in practical risk management in Islamic finance. First, the effect of shariah-compliant strategy to portfolio optimization is covered in the literature review. After analyzing the literature, it was identified that the previous models lack the fuzzy environment so that they were unable to deal with uncertainty. Consequently, a new model is proposed to apply the fuzzy environment to Shariah-compliance portfolio optimization. In this research activity, an E-S model by the linear combination of the risk and reward for fuzzy shariah-compliant is proposed. Finally, some future works are presented along with a conclusion.

This paper examines the use of the Four Point-Explicit Decoupled Group (EDG) iterative method together with MSOR iterative method, namely 4 Point-

EDGMSOR

. The efficiency of this method will be investigated to solve two-dimensional Helmholtz equation by using half-sweep finite difference approximation. In fact, the formulation of and implementation of the proposed method are also presented. Some numerical examples are presented to point out efficiency of the proposed method.

Complex event processing received an increasing interest during the last years with the adoption of event-driven architectures in various application domains. Despite a number of solutions that can process events in near real-time, their effectiveness for decision support relies heavily upon human domain knowledge. This poses a problem in areas that require vast amounts of specialized knowledge and background information, such as medical environments. We propose four techniques to enrich complex event processing with domain knowledge from ontologies to overcome this limitation. These techniques focus on preserving the strengths of state-of-the-art systems and enhancing them with existing ontologies to increase accuracy and effectiveness. The viability of our approach is demonstrated in a multifaceted experiment.

In this paper, an improved User Parameter Control (UPC) algorithm is proposed to control traffic in ATM networks. The algorithm consists of delay elements such as Cell Buffer, Red Token Pool, Green Token Pool, and Dynamic Spacer. The token here is used to control traffics rather than to arbitrate the contention of buses. A token is generated during a random time period, and the accumulated tokens are consumed one each time a cell arrives. At this time, if the delay element, named Dynamic Spacer, is empty, the cell comes into the network. On the other hand, if the Spacer is not empty, the cell cannot come into the network. In addition, in the case that tokens do not exist in Token Pool, the corresponding cell is thrown away. This research proposes new UPC Algorithm to improve the cell delay rate and cell loss rate by adopting Dynamic Spacer. The proposed algorithm dynamically controls traffic in ATM networks with respect to the various traffic status.

The achromatic number for a graph

G

= (

V

,

E

) is the largest integer

m

such that there is a partition of

V

into disjoint independent sets (

V

1

, ... ,

V

m

) such that for each pair of distinct sets

V

i

,

V

j

,

V

i

∪

V

j

is not an independent set in

G

In this paper we present an

0

(1)-approximation algorithm to determine the achromatic number of Hex derived networks.

Local Polynomial Wavelet Shrinkage estimator (LPWS) is an attractive technique used to cope with the boundary problem present in wavelet shrinkage. However, this combined estimator seems to be quite sensitive to the presence of correlated noise. In this paper, the practical consequences of this sensitivity are explained; including the breakdown of several popular thresholding selection methods. The term-by term level dependent thresholding has been investigated as an effective solution for recovering a signal contaminated with correlated noise. A simulation study is conducted to evaluate both EbayesThresh and level dependent cross validation under a variety of test function, noise structure, signal to noise ratio and sample size. Results showed that thresholding by level dependent cross validation is preferable.

There has been an alarming increase in demand for highly efficient and reliable scheme to ultimately support delay sensitive application and provide the necessary quality of service (QoS) needed. Multimedia applications are very susceptible to delay and its high bandwidth requirement. Consequently, it requires more sophisticated and low complexity algorithm to mitigate the aforementioned problems. In order to strategically select best optimal solution, there is dramatic need for efficient and effective optimization scheme to satisfy different QoS requirements in order to enhance the network performance. Multi-objective particle swarm optimization can be extremely useful and important in delay and mission-critical application. This is primarily due to its simplicity, high convergence and searching capability. In this paper, an optimal parameter selection strategy for time stringent application using particle swarm optimization has been proposed. The experimental result through well-known test functions clearly shows that multi-objective particle swarm optimization algorithm has extremely low computational time and it can be potentially applicable for delay sensitive applications.

Given a graph

G

(

V

,

E

), a labeling ∂:

V

 ∪ 

E

 → {1, 2...

k

} is called an

edge

irregular

total

k

 − 

labeling

if for every pair of distinct edges

uv

and

xy

, ∂ (

u

) + ∂ (

uv

) + ∂ (

v

) ≠ ∂ (

x

) + ∂ (

y

) + ∂ (

xy

). The minimum

k

for which

G

has an edge irregular total

k

-labeling is called the

total

edge

irregularity

strength

of

G

. In this paper we examine the total edge irregularity strength of the butterfly and the benes network.

Today, many organizations have implemented knowledge management system (KMS) to facilitate activities in achieving their business objective and goal. Despite of the benefits that have been given by the system, its adoption and frequent use remain challenges. As acknowledged that KMS adoption is a complicated and context dependent, it is merit to investigate in understanding the phenomenon in a real setting. The purpose of this paper is to understand the nature of KMS adoption and diffusion in organization with the aim to provide recommendations which helping to increase adoption and utilization. The generated grounded results offer not only the identified factors and processes that could possibly lead to adoption but also those that make its diffusion and finally become part of daily practice.

Medical Imaging is an application of image processing in which normalization is one of the important process involved in most of the medical image analysis. Normalization is the process of mapping source image with same stereotaxic space. This can be done by registering each image to the same template, where template can be constructed by considering average of large number of high resolution MRImages. Normalizing source image with common existing template will help in analyzing inter subject relationships based on various factors, such as, age, sex etc. But for analyzing single patient data, normalization step can be skipped by registering source image with subject’s/patient’s anatomical data. Since there may be a variation between template and subject data, normalization step may either stretch or shrink the source image, where there are high chances of shift in motor activation area. This paper proves with experimental results of a trivial example of a subject, where normalization step have to be ignored for single subject analysis.

Cooper and Wadler introduced the RPC calculus, which is obtained by incorporating a mechanism for remote procedure calls (RPC) into the lambda calculus. The location where a caller’s code is executed is designated in a lambda abstraction in the RPC calculus. Nishizaki et al. proposed a simplified abstract machine for the lambda calculus, known as a Simple Abstract Machine (SAM). The configuration of an SECD machine is a quadruple of data sequences: Stack, Environment, Code, and Dump. In contrast, the SAM configuration is a double of data sequences: Stack and Code. In this paper, we introduce a SAM-based abstract machine for the RPC calculus, called a Location-aware Simple Abstract Machine (LSAM). This machine makes it possible to model parallelism more clearly. We provide a translation of the RPC calculus into LSAM, and prove a correctness theorem for the translation. We then show that the translation can be extended to allow parallel execution in LSAM.

The performance of data processing in distributed information systems strongly depends on the efficient scheduling of the applications that access data at the remote sites. This work assumes a typical model of distributed information system where a central site is connected to a number of remote and highly autonomous remote sites. An application started by a user at a central site is decomposed into several data processing tasks to be independently processed at the remote sites. The objective of this work is to find a method for optimization of task processing schedules at a central site. We define an abstract model of data and a system of operations that implements the data processing tasks. Our abstract data model is general enough to represent many specific data models. We show how an entirely parallel schedule can be transformed into a more optimal hybrid schedule where certain tasks are processed simultaneously while the other tasks are processed sequentially. The transformations proposed in this work are guided by the cost-based optimization model whose objective is to reduce the total data transmission time between the remote sites and a central site. We show how the properties of data integration expressions can be used to find more efficient schedules of data processing tasks in distributed information systems.

In this paper, we consider a class of connected planar 3-regular graphs (rotation systems) and show that, for any two such graphs with the same number of vertices, one kind of local rewriting rule is capable of rewriting one graph to the other. On the basis of such graph development systems, emergent systems including self-organizing systems will be considered in a uniform manner.

Traditional query routing mechanisms for service and resource discovery in distributed systems function purely at the overlay layer by isolating itself from the underlying IP-layer. This leads to large amount of inter-ISP traffic and unbalanced utilization of underlying links which affect the performance of the network. In this paper we address this problem by proposing a novel distributed service discovery algorithm, which enables IP-layer awareness so that query routing is performed without the involvement of the overlay peers. In our algorithm, message level intelligence is exploited using Application Oriented Networking (AON) and thus query forwarding is performed in the IP layer. We also classify services in the registry based on industries so that queries could be forwarded selectively. We present the conceptual design of our framework and analyze its effectiveness through simulation. Our simulation results prove the performance gain obtained by moving down the overlay query routing mechanism to the IP-layer.

Grid Computing handles huge amount of data which is stored in geographically distributed sites. It is a great challenge to ensure that data is managed, distributed and accessed efficiently in the distributed systems such as the data grid. To address the challenge, various techniques have been proposed in the literature. One of the widely used techniques is data replication since it offers high data availability, fault-tolerance and improve the performance of the system. In replication-based systems, replica control protocols are implemented for managing and accessing the data. In this paper, we present a comparison of various quorum-based replica control protocols that have been proposed in the distributed environment. This paper attempts to compare these replica control protocols based on the strengths, weaknesses and performance of the protocols.

In this paper, we present a methodology for managing the Distributed Virtual Memory (DVM). The methodology includes distributed algorithms for DVM management to detect the memory status which will enhance previous DVM techniques. The DVM data structure tables are similar to those found in current Conventional Virtual Memory (CVM) with some modifications. Finally, we evaluate our methodology through experimental results to show the effectiveness of our approach.

Let

G

 = (

V

,

E

) be a graph with vertex set

V

and edge set

E

. Let

diam

(

G

) denote the diameter of

G

and

d

(

u

,

v

) denote the distance between the vertices

u

and

v

in

G

. An antipodal labeling of

G

with diameter

d

is a function

f

that assigns to each vertex

u

, a positive integer

f

(

u

), such that

d

(

u

,

v

) + |

f

(

u

) –

f

(

v

)| ≥

d

, for all

u

,

v

 ∈ 

V

. The span of an antipodal labeling

f

is

max

{|

f

(

u

) –

f

(

v

)|:

u

,

v

 ∈ 

V

(

G

)}. The antipodal number for

G

, denoted by

an

(

G

), is the minimum span of all antipodal labelings of

G

. Determining the antipodal number of a graph

G

is an NP-complete problem. In this paper we determine the antipodal number of certain graphs.

Graph partitioning has several important applications in Computer Science, including VLSI circuit layout, image processing, solving sparse linear systems, computing fill-reducing orderings for sparse matrices, and distributing workloads for parallel computation. In this paper we have determined the induced matching partition number for certain classes of bipartite graphs, sierpinski graphs, sierpinski gaskets, honeycomb tori and honeycomb networks.

The

PI

index of a graph

G

is defined as

PI

(

G

) = Σ[

η

eu

(e|G) +

η

ev

(e|G), where for the edge

e

= (

u

,

v

),

η

eu

(e|G) is the number of edges of

G

lying closer to

u

than

v

;

η

ev

(e|G) is the number of edges of

G

lying closer to

v

than

u

and summation goes over all edges of

G

. In this paper, we have introduced a new strategy to compute

PI

indices of graphs. Using this strategy, the

PI

index of mesh, torus and honeycomb mesh,

NaCl

molecule and benzenoid graph have been computed.

Graphics processing units (GPUs) offer great potential for accelerating processing for a wide range of scientific and business applications. However, complexities associated with using GPU technology have limited its use in applications. This paper reviews earlier approaches improving GPU accessibility, and explores how integration with middleware messaging technologies can further improve the accessibility and usability of GPU-enabled platforms. The results of a proof-of-concept integration between an open-source messaging middleware platform and a general-purpose GPU platform using the CUDA framework are presented. Additional applications of this technique are identified and discussed as potential areas for further research.

The wide diameter of a graph is a natural generalization of diameter in a graph when we take account of the connectivity of the graph. The concept of wide diameter has been discussed and used in practical applications, especially in the distributed and parallel computer networks. In this paper, we find the wide diameter of generalized fat tree. Moreover we obtain the bisection width of generalized fat tree.

In this paper a new pyramidal topology for multicomputer interconnection networks based on the sierpinski gasket network is proposed. The Sierpinski fractal or Sierpinski gasket is a familiar object studied by specialists in dynamical systems and probability. The new network is referred to as the sierpinski gasket pyramid. We study the topological properties such as connectivity, diameter, chromatic number, hamiltonicity, pancyclicity and

K

4

-decomposition of the new pyramid network.

The crossing number of a graph

G

is the minimum number of crossings of its edges among the drawings of

G

in the plane and is denoted by

cr

(

G

). Bhatt and Leighton proved that the crossing number of a network is closely related to the minimum layout area required for the implementation of the VLSI circuit for that network. In this paper, we find an upper bound for the crossing number of a special case of the generalized fat tree based on the underlying graph model found in the literature. We also improve this bound for a new drawing of the same structure. The proofs are based on the drawing rules introduced in this paper.

Wireless sensor networks (WSNs) have been increasingly deployed for ambient data reporting for varied settings. Certain applications like industrial monitoring, healthcare and military require a highly reliable source to the sink communication link. Due to limited energy WSNs pose additional challenge to the reliable source to the sink communication. Fast energy drainage can cause a link failure, hence affecting the overall reliability. In this paper, a novel three tiered multi-hop scheme has been introduced. At first level there are sensor nodes for sensing, at second level there are relay nodes for relaying and at the third level there are gateway nodes for managing the cluster and communicating to and from the cluster. By distributing the load among these three tiered nodes, overall node and network lifetime can be greatly increased. With the help of reduced energy consumption and less end-to-end hops this schemes guarantees a reliable source to the sink communication.

In this paper we propose the integration of computer vision with accelerometry and the magnetometer and radios available in current state-of-the-art smart phones, in order to provide a precise localization solution feasible for indoor environments. In terms of accelerometry, we apply the wavelet transform to the signal of a single off-the-shelf accelerometer on the waist to obtain the velocity and stride length of the user. This allows us to link accelerometry and computer vision through the kinetic energy of the user. Additionally, our system leverages the capabilities of current state-of-the-art smart phones to integrate both offline and online phases of radio fingerprinting with WiFi, achieving an accuracy of 1.5 meters. We have also studied the possibilities offered by the cellular communications radio, with the intention to build a multimodal solution for localization, delivering an accuracy of up to 0.5 meters when all the information is combined with a Kalman filter.

In this paper, we develop an analytical model of the signaling costs due to location update and paging for the radio interface in mobile communications networks. This model accounts for the effects that the savings brought by different algorithms have on the total Location Management (LM) costs. It also takes into account the trade-off between the location update and paging costs, showing that those strategies that achieve savings in the location update costs deliver a larger overall improvement in the total LM costs than those algorithms focusing on the minimization of the paging costs. Moreover, leveraging the factors studied to obtain this model, we also analyze the overall LM costs including the fixed network part.

Audio-visual information is one of the richest but also most bandwidth-consuming modes of communication. To meet the requirements of new applications, powerful data compression schemes are needed to reduce the global bit rate drastically. In this paper, we proposed a simple lossless visual image compression scheme that will be used to compress visual images. In this scheme, the two dimensional visual image data is converted to a one dimensional data using our proposed pixel scanning method. The difference between consecutive pixel values in the resulting one dimensional image data is taken and the residues are encoded losslessly using an entropy encoder. The working principles of this our approach is presented together with the image compression algorithm used. We developed a software algorithm and implemented it to compress some standard test images using Huffman style coding techniques in a MATLAB platform.

Energy competence is a very important study in order to find ways to prolong the lifetime of a wireless sensor network. Therefore a good routing protocol and mechanism need to be design. Cluster based architecture is a well known method to optimize the energy competence in the network and have been applied in LEACH routing protocol. However the LEACH routing protocol that used a round concept have a problem because each node will suffer its rest energy in the current round and will die in the next round due to insufficient energy management in the network. Then, we make an alteration of LEACH’s cluster-head selection algorithm by considering an outstanding energy available in each node in order to extend the lifetime of the network. It is known as the Residual Energy (ResEn) algorithm. Consequently, at the end of this paper a comparison analysis for LEACH and ResEn has been simulated using Matlab. As a result, it shows that ResEn algorithm can extended the lifetime of the network.

Bluetooth is a low cost wireless technology for short range device. The Bluetooth system can be used for different kinds of data exchange; it carries both synchronous and asynchronous data traffic. Bluetooth basic network is called piconet; multiple connected piconets are called scatternet. The scatternet structure has a great impact on the network performance. Without considering the traffic flow, a scatternet may suffer from serious congestion problem. The objective of this research work is to propose a new Bluetooth Inter-piconet Congestion Avoidance (ICA) protocol by network restructuring. The main objectives of proposed protocol are to share the traffic load and find the shortest routing path for pairs of Bluetooth sources and destinations. Simulation results show that proposed protocol reduces control overhead, decreases delay and improves network throughput.

Voice over IP (VoIP) or IP telephony is a very popular way of communication not only for single users but also for big enterprises. Due to fast-growing wireless technology and ease of use of wireless networks, VoIP is now being deployed over Wireless LANs (VoWLANs). The main issues in communication of real time application on IP networks, however, are providing Quality of Service (QoS), security and capacity. Capacity planning is an essential factor to consider at the time of developing VoIP network. Wireless links provide different capacity due to multi-rate transmission that affects all active calls. This paper focuses on the capacity problem and attempts to determine the maximum number of calls the bandwidth can support in each transmission rate based on different speech codecs and packetization intervals.

For ad hoc networks, clustering is the organization method that groups the nodes into clusters managed by nodes called cluster-heads. This hierarchical organization allows an effective way of improving performance, security, fault tolerance and scalability of the platform. In this paper, we introduce a new approach to self-organize an ad hoc network, and define communication protocols so that to optimize communication in the routing. We implement a hierarchy structure to the ad hoc network, that is: many clusters with one leader per group, and a coordinator for the whole network. In order to optimize the communication process, decent metrics are chosen in group formation and in leader election. To illustrate the performance of our algorithm, we verify it using model checking; we simulate it and compare its performance with a geographical-based algorithm.

The controller area network (CAN) has been long regarded as the pioneer in standardizing vehicle bus standard. Its influence has even been reached out to various applications in industrial automation; which includes military, aviation, electronics and many others. With wireless technology becoming more pervasive, there is a need for CAN too to migrate and evolve to its wireless counterpart. In this paper, a new wireless protocol named wireless controller area network (WCAN) is introduced. WCAN is an adaptation of its wired cousin, controller area network (CAN) protocol which has not being properly defined. The proposed WCAN uses the concept introduced in wireless token ring protocol (WTRP); a MAC protocol for wireless networks and efficient in a sense to reduce the number of retransmission due to collisions. Additionally, it follows most of its wired cousin attributes on message-based communication. Message with higher priority has the first priority in transmitting their message into the medium. In WCAN, stations or nodes take turns in transmitting upon receiving the token frame that are circulating around the network for a specified amount of time. WCAN was tested in a simulation environment and is found that it outperform IEEE 802.11 in a ring network environment.

The use of the low-dropout (LDO) voltage regulator in reducing current consumption in the active tag RFID system using the ZigBee standard was studied. The tag was set with a cyclic mode configuration with non-beacon data transmission mode, and was programmed to sleep for 1.5 s and wake up for 5 s to check for signals coming from the reader. The LDO voltage regulator from the TPS7800 series with ultra-low quiescent current was used in the experiments. Two sets of experiments were conducted using tags with and without LDO voltage regulators, respectively. The current consumed by the active tag was measured, and the results showed that the current consumption was reduced to 32% if the LDO was used to regulate the input voltage from 3 V to 2.2 V. The current consumption remained stable although the voltage source dropped from 3 to 1.8 V. The transmission range also increased when the LDO was adopted in the system.

In distributed sensor networks, a large number of small sensors are deployed to create a network which cooperates together to set up a sensing network. The main duty of sensors is to prepare access to environmental information anytime, anywhere by collecting, processing, analyzing and transmitting data. Scalability, load balancing and increasing network lifetime are significant parameters for wireless sensor networks [1]. Clustering is a useful technique to address these issues. In this paper, we propose a distributed, energy-efficient, fault tolerant and weighted clustering algorithm that extends the network lifetime by using some parameters such as energy, centrality, density, in addition distances between nodes and the base station. We consider a backup node for each cluster, that will be replaced while the cluster head drain out of its energy, and also cluster head list [2] for every node. These mechanisms cause increasing the network lifetime and lead the network to become fault tolerant.

The research is on the location estimation and filtering of wireless nodes in an open environment. This research is based on our previous findings in which we categorized the geographical area into thirteen different terrains/clutters based on the signal to noise ratio. As signal to noise ratio differs from terrain to terrain therefore data points are calculated for each terrain. A C# program is used with the WiFi architecture to calculate the available signal strength and the receive signal strength. Estimation is done by using triangulation method with the construction of three triangles. As each experiment is repeated five times which estimated five different positions due to the effect of signal to noise ratio, therefore fifteen locations are estimated based on three triangles. Filtering is further done by using average and mean of means calculations. Results show that terrains/clutters based location estimation and filtering produce better results. Only terrains with high attenuation such as sea, dense forest, highway/motorway and high dense urban areas has high error rate after filtering. This research work helps to minimize location error in an open environment.

Medium access control (MAC) protocols in a cognitive radio network (CRN) are required to increase spectral efficiency and achieve high data rate for secondary users (SUs). Many MAC protocols use a single control channel with a bottleneck problem. In this paper, we propose a multichannel MAC protocol using dicontiguous orthogonal frequency division multiplexing (D-OFDM) in a CRN. Since D-OFDM technology enables SUs to receive multiple packets on discontiguous multiple channels, the proposed MAC protocol adopting D-OFDM has an effect of utilizing multiple control channels, which mitigates the control channel bottleneck problem. Simulations show that the throughput of the proposed protocol outperforms the split phase control channel (SPCC) approach.

Recently mobile communication systems such as 3GPP LTE, IEEE802.16e have been growing interest in the femto-cell systems for increase of data rates and enhanced call quality. Cell management method for handover in a femto-cell system is very important issue because it includes heavy control management information of macro-cell and a large number of femto-cells and can be a burden to a system. In this paper, we propose an adaptive construction of control management message (MOB_NBR-ADV) and cell management method in a femto-cell system. The proposed scheme provides fast scanning and efficient handover by means of preselecting the candidate target femto-cells. The simulation results show that the proposed schemes improve the MS’s handover-related performance in terms of scanning power and scanning time compared with the conventional management scheme of femto-cell systems.

Underwater Wireless Sensor networks (UWSNs) comprised of a number of sensor nodes that are deployed to perform collaborative monitoring tasks. Sensor nodes are connected to each other through wireless signals. Acoustic signal is the dominant wave used for UWSNs communications. Acoustic signals face a lot of challenges such as ambient noise, manmade noise, limited bandwidth, multipath and low propagation speed. These challenges become more severe in shallow water environment where a high level of ambient and manmade noise, turbidity and multipath is available. Therefore, Electromagnetic signals can be applied for using as a communication signal for UWSNs. In this work, the performance of electromagnetic communication in the water environment is investigated. The investigation is conducted for fresh and seawater environment. Results show that freshwater environment can permit short range communication while the communication is more difficult for seawater due to the high value of attenuation.

Relay-assisted cellular network is a major concern in research studies around the world as it can aid the cell to achieve coverage extension and capacity enhancement. Long Term Evolution-Advanced (LTE-A), a candidate from Third Generation Partnership Project (3GPP) has include relaying as one of its key technologies to meet International Mobile Telecommunications (IMT) Advanced requirements. This article focuses on relay architectures from LTE-A and the types of relay defined in the standard. Pros and cons of developed relaying strategies, transmission schemes together with relay selection pairing scheme are also reviewed. This article also provides simulation results comparing performance between transmission with and without the usage of relay. In addition, recent studies extending the relaying concept such as cognitive and cooperative relaying as a hot research topic are also discussed.

RFID tags are becoming more and more widespread, but their privacy issue has remained yet as a major concern. Due to resource limitations on these tags, providing the privacy is challenging while it is undoubtedly critical before their full deployment. A considerable number of protocols have been proposed, improved over the time and crypt analyzed to provide descent solutions to RFID privacy problem, each of which with strengths and weaknesses. This paper addresses privacy weaknesses of some of them and in the main part of this paper; we propose a scalable anonymous RFID authentication protocol and describe its design and implementation issues. Our protocol mainly substitutes the hash function used for identification with anonymous tickets, which uniquely identify tags and are reusable. As the result, it considerably strengthens untraceability feature and it needs just O(1) search time and query with small storage overhead on the back-end system.

Coordinated Multi-Point (CoMP) transmission and reception is seen as a promising technology to achieve higher spectral efficiency in LTE-Advanced systems. Base stations cooperation can be one of the most important enabling technologies beneficial in scenarios with high inter-cell interference (ICI). In this paper, interference mitigation and coordination schemes in CoMP are being discussed. Simulation study to show the significant effect of ICI to cell-edge performance is presented. In this work, we proposed an interference cancellation scheme with minimal backhaul requirements in addition to existing inter-cell interference coordination (ICIC) schemes.

Cognitive Radio (CR) is a promising technology in wireless communication for an enhanced utilization of limited spectral resources. It allows unlicensed or cognitive users (CUs) to sense the spectral environment and access a channel exhibiting negligible activity of licensed or primary users (PUs). Hence, spectrum sensing is a crucial task for a CU to perform in an opportunistic spectrum access (OSA) based CR network to avoid harmful interference to PU. Two main performances metrics that are crucial in the design of spectrum sensing are the probability of false alarm (

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and

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curves based on locally captured data to determine the value of the threshold and sensing time. The implementation, experimentation and measurement are done using GNU Radio and universal software defined radio peripheral (USRP) software defined radio (SDR) platform as the cognitive radio testbed. Spectrum sensing was done based on energy detection. Each of the energy based detection measurement is repeated 1000 times to obtain an accurate estimation of

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and

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. The findings show that the target Quality of Sevice (QoS) of

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of 5% and

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of 90% can be derived from the estimated sensing threshold of -39 dB and achieves a sensing time of 31.59 ms.

Wireless Sensor Network (WSN) consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different location for the intended user. One of its potential deployments is in the form of Wireless Biomedical Sensor Network (WBSN) to measure physiological signals. The WBSN applications would allow the medical practitioners to continuously monitor and update the status of a patient remotely. This paper focuses on the development of a wireless sensor node platform for WBSN application which complies with IEEE 802.15.4 standard and operates in 2.4 GHz ISM (industrial, scientific and medical) band. The initial state of WBSN development is the design of the wireless sensor node called TelG. The main features of TelG include low power consumption, wearable, flexible and small size. It is then embedded with a self-built operating system called WiseOS to support customized operations.

Transmission Control Protocol (TCP) is the dominant protocol used in the Internet today. It was well designed to work over a wired network. However, TCP suffers from performance degradation in a wireless ad-hoc network. The main reason is that regular TCP misinterprets packet loss due to wireless channel error as network congestion and consequently reduces its sending rate,. In this paper, we propose a new end-to-end mechanism to support TCP discriminating congestion loss from none-congestion loss. The proposed mechanism is evaluated using simulation under different network topologies and varying PER levels; results demonstrate that the proposed scheme outperforms NewReno, in terms of throughput, by 30%.

Exponential increase in demands of wireless access over the years has led to rapid evolution for next generation wireless access technology. However, with scarce spectrum resource yet increasing bandwidth demand has become the main concern since this problem will hinder the evolution process and generally affects network performance. In this paper, by taking 3GPP (3rd Generation Partnership Project) LTE-Advanced (Long Term Evolution - Advanced) as a perfect specimen for 4G (fourth generation) standard candidate, we thoroughly investigate its key technologies thus providing overviews on network performance and efficiency improvement by implementing cooperative communication and cognitive radio (CR) technology.

The paper “Communications in Computer and Information Science: A New Scalable Anonymous Authentication Protocol for RFID” authored by Mohammad Shirafkan, Naser Modiri, Mohammad Mansour Riahi Kashani, and Koosha Sadeghi Oskooyee, DOI 10.1007/978-3-642-25462-8_57, appearing on pages 639-653 of this publication has been retracted due to a severe case of plagiarism. It is a plagiarized version of the paper ‘A Privacy-Friendly RFID Protocol Using Reusable Anonymous Tickets’, authored by Mahdi Asadpour and Mohammad Torabi Dashti, published in the proceedings of the 10th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2011), DOI 10.1109/TrustCom.2011.29 and of the master thesis ‘An Anonymous RFID Authentication Protocol and its Automated Analysis with OFMC’ completed by Mahdi Asadpour at ETH Zurich.