Advances in Ubiquitous Networking

We consider the uplink case of a cellular system where m bufferless mobiles transmit over a common channel to a base station, using the slotted aloha medium access protocol. We study the performance of this system under a new transmission scheduling scheme. In contrast to slotted aloha, each new arrival packet is first transmitted at a probability $$p_a$$ and retransmitted later, if needed, with probability $$q_r$$. Under this proposal, we analyze the cooperative team in which a common goal is jointly optimized. Later, we derive the average throughput and the expected delay and use them as the objectives to optimize. We further study the impact of parameters on the average throughput as well as the expected delay. Furthermore, we address the stability behavior of our new scheme. We finally carry out extensive numerical examples to illustrate the obtained gain which concerns, in particular, the expected delay minimization.

Due to the growing needs of positioning solutions serving for both emergency cases and daily life uses, many researches are carried out to enhance the existing techniques in a way to find a robust method that meets the expectations of both areas. In this paper, we propose an enhanced hybrid approach between the up-link time difference of arrival and Assisted GPS positioning methods for UMTS users by improving the accuracy of UTDOA using the NLMS adaptive filter instead of usual filter before performing the cross-correlation.

In the decentralized networks, interactions among selfish users sharing a common transmission channel can be modeled as a non cooperative game using game theory. When selfish users choose their transmission probabilities independently without any coordination mechanism, Nash equilibria leads to a suboptimal use of the channel resource and to the degradation of the performance of MAC protocols. In this paper we transform the non cooperative game in a general Stackelebrg game when multiple leaders and followers coexist and competitively maximize their own function utilities. Under a simple multiple power levels scheme, the new Stackleberg equilibrium can overcome the deficiency of the Nash equilibrium as well as the limited efficiency of the Sackelberg contention game when the users transmit using a single power level. The power control is defined in such way that the leaders choose the lowest power to transmit their packets among N available levels whereas the followers retransmit at the random power levels picked from $$N-1$$ higher distinct. Furthermore, we investigate the impact of the implementation of our scheme on the equilibrium and discuss the optimal partition of leaders/followers to achieve better performance. We further show that the hierarchical system is performing better as the number of leaders is small.

In this paper, we consider the decentralized scenario of spectrum leasing, whereby a primary user (PU) who owns the spectrum resource, may lease a part of her licensed spectrum to a secondary (SU). We propose a pricing-based spectrum leasing framework between the PU and the SU. The spectrum leasing problem can be depicted by a non-cooperative game where: on one hand, the PU plays the seller and attempts to maximize its own utility by setting the price of spectrum. On the other hand, the SU (i.e., the buyer) has to decide whether to accept the leasing offer or to decline it, while seeking to maximize her own utility. Next, we characterize the Nash equilibria of the induced game for both pure strategies and mixed mixed strategies. We also propose numerous learning algorithms that allow cognitive users to learn their optimal strategies and payoffs for both continuous and discontinuous actions. Simulation results evaluate our model and show the behaviour (accuracy and speed of convergence) of the proposed learning algorithms.

In this paper, we present a theoretical analysis of bit error rate (BER) for asynchronous filter bank multicarrier (FBMC) based multi-cellular networks in the presence of high power amplifiers (HPA) nonlinear distortion (NLD). A promising class of FBMC modulation called Cosine Modulated Multitone (CMT) is considered and the analytical BER is derived based on the signal to interference plus noise ratio (SINR) of a cellular network consisting of one reference mobile user (MU), one reference base station (BS) and K interfering BSs. The proposed model is evaluated and it is found in very good agreement with simulation results.

Currently in the literature, there is a significant number of access methods to the shared communication channel. For this purpose, two major classes of protocols are defined: controlled access protocols and competing protocols, in which our work is registered. In our paper, we define an access protocol where each station possesses a different and unique contention sequence CS, with which they enter in a battle with other stations. In the end of the competition, only one station is identified as a winner, and will be allowed to access to the channel and transmit its information successfully without any risk of failure. This technique is named zero failure access ZFA.The object of this paper is to compare the present technique ZFA with the other existing techniques and access methods, for instance slotted ALOHA and DCF protocols. For this issue, we derive the throughput for the three different access methods and finally illustrate the results by simulation.

Cloud computing is the new technology in open and distributed systems, recently adopted by many IT companies and business organizations. In such systems, there are usually a large number of users in different domains having their own policies, which make many problems arise as degradation or loss of information access control, theft or unauthorized use of information, as well as quality of services problems, traceability and accountability. Data access using various resources requires a user authentication, access control model for integrated management and control in cloud computing environments. The traditional access control models that are identity based are closed and inflexible. In this paper we present an overview of access control models with comparative and analysis to retrieve a suitable model for such environment. An extended Attribute based Access Control (ABAC) model is proposed by introducing the concept of privacy aware to retrieve a new efficient advanced model that can provide a more flexible, privacy and integrity model.

With the growing popularity of Internet-enabled devices, the impressive progress in sensing technology, and the adoption of cloud computing for provisioning services, users increasingly demand services that can adapt to their recent context. In this paper, we propose a multi-attributes and adaptive approach for Context Level Agreements (CLAs) negotiation between a context provider and a context consumer using a context broker. The approach employs a Nash bargaining model and evaluates the global utility of each party as a linear function of normalized Quality of Context (QoC) attributes during the rounds of negotiation. The ultimate goal is to improve context-based adaptation of context-aware applications and services. One of the advantages of this approach is that it permits to resolve conflicts of interests between the context provider and the context consumer when the global utility of each party reaches a Pareto optimum.

Cloud computing is a new model of computing which provides scalability, flexibility and on-demand service. Virtualization is one of the main components of the cloud, but unfortunately this technology suffers from many security vulnerabilities. The main purpose of this paper is to present a new secure architecture of Virtual Network machines in order to increase security among virtual machines in a virtualized environment (Xen as a case study). First, we expose the different network modes based on Xen Hypervisor, and then we analyses vulnerabilities and security issues within these kind of environment. Finally, we present in details new secure architecture and demonstrate how it can face the main security network attacks.

Mobile devices, such as tablets and smartphones, have become the main computing platform for many people. Ubiquitous computing, as a concept, has developed with the emerging of cloud computing technology that has forced the mobile devices industry to prerequisite the bringing of cloud computing to mobile domain. Mobile Cloud Computing MCC is a service that allows users of mobile devices high availability of their personal applications as well as their own content, everywhere and anytime. Unfortunately, malicious people take advantage of this technological achievement in the sense that they store all illegal information on cloud in order to hide all digital illegal records justifying their illicit acts served by their mobile devices. What is more, mobile forensic expertise on those mobile devices cannot be accomplished by digital investigators of law enforcement, simply because all the storage is done in the cloud. In this vein, Mobile Cloud Computing MCC technology is a double-edged weapon; it has made life easier on one hand. And, it has complicated the work of law enforcement authorities to find truth, on the other hand. In cloud environment, malicious users can be stored several and various formats of suspicious content (text, image, video…), so in this work we will focus only on textual content. Text mining is an effective way to add semantics aspect to this communication’s form presenting a significant research challenge. Similarity approach is used in text analysis to detect suspicious text contents in cloud storage. So, in this paper we will present a state-of-the-art and research challenges of mobile cloud computing. We will also discuss the problem of data management and data analysis on a cloud environment. Ultimately, we will suggest an approach to come up with the aforementioned problems.

E-learning is a new method of learning which depends on the Internet in its execution. Nowday’s e-learning’s popularity is increasing as more and more people are taking online courses. It becomes the need of the hour, since it is being used as a big platform for enhancing and upgrading knowledge by increasing flexibility in various fields and providing ways to make learning easier. However E-learning has several challenges, one of these major challenges is Information Security. The security aspect is even more important for controlling access to information resources intended to specific users depending on several predefined contexts. Defining such access control is directly related to the appliance of a control access policy, responsible of securing learning sessions in an e-learning platform.The purpose of this paper is to propose how to adapt ORBAC (organization role based access control) model which is considered as one of the most developed access control security models, to improve the highest degree of security in a concrete e-learning scenario for educational purpose, and to prove how the expressive power and flexibility of this model work. The proposed approach is implemented and evaluated by simulation using “MotOrbac” tool in order to define its validity context and limitations for a large and extended deployment.

This paper proposes a simple, secure, and privacy-preserving architecture for inter-Cloud data sharing based on an encryption/decryption algorithm which aims to protect the data stored in the cloud from the unauthorized access.

The cloud computing is a new trending paradigm that presents several benefits in achieving rapid and scalable resource provisioning capabilities to their users. Despite the fact that cloud computing offers many cost benefits for their cloud users, number of security risk are emerging in association with cloud usage that need to be assessed. Assessing risk in Cloud computing environment remains an open research issue. This paper presents a comprehensive and shared risk assessment method for cloud computing that will add a great help and assistance to both cloud consumers and cloud providers, which is also in compliance with all the specific characteristics of the Cloud Computing. An experimental result will be showed at the end to demonstrate the effectiveness of this new risk assessment model.

This paper presents the behavior of three iterations of a CoPlanar Waveguide-fed (CPW) CANTOR Set fractal antenna. This kind of antennas allows having an Ultra Wide Band (UWB) behavior and important gains. Also, the setup of slots allows having more lower resonant frequencies and therefore designing miniaturized antennas with good performances.All the simulations were performed with FEKO 6.3.

Beam-steering antenna is the ideal solution for a variety of system applications, it is most commonly achieved through using phased array, where phase shifters are used to control the relative of the main-beam. However this technique cannot be used in the mobile terminals which use only single radiation element. In this work we present a high directivity and beam steering antenna using simple printed patch covered by adjustable left handed metamaterial superstrate. The design and simulations are carried out using HFSS software.The adjustable metamaterial is based on double omega shaped unit cell. The antenna used is a probe feed rectangular microstrip patch which operates at X band. An appropriate loading of the metamaterial unit cell, through the use of a varactor diodes, enables to vary the medium index of the superstrate within an interesting range, therefore ± 30° deflection of the antenna beam is obtained. Furthermore, using metamaterial superstrate, the antenna performance has been improved significantly, indicating that the directivity can achieve 11.31 dBi and the HPBW is about 23° for all beam-steering angles.

In this paper a planar rectenna (rectifier + antenna) design which is the crucial part in a microwave power transmission system is presented. The developed structure is suitable to harvest RF energy at 5.8GHz ISM frequency band for powering devices involving low power consumption, located in unreachable area or needing expensive maintenance costs. The proposed design incorporate a 2 × 2 circular polarized antenna array with an enhanced directivity of about 10.2 dBi and an overall size of 14.6 × 8 cm2 built and carried out by using CST Microwave Studio software. The receiving antenna is associated with a microstrip rectifier that combines series and shunt configuration employed Schottky diode HSMS2852 and HSMS2850. The RF-to-DC rectifier circuit is designed and simulated by using schematic simulation in ADS software. An output DC voltage of 2.2 V and a RF-to-DC conversion efficiency of more than 70% were achieved with an optimum load resistance of 6 kΩ for 0 dBm microwave incident power level.

This paper presents a miniaturized flexible microstrip antenna designed using a Liquid crystal polymer (LCP) material. The developed design consists on a hexagon radiator with two ring slots excited by a CPW feed line, providing an operating frequency in S-band at 3GHz with an important bandwidth of 600MHz. This structure offers a thin thickness (1.6mm) with an overall size of 30×20 mm2 that’s can assure an easy integration into clothes as wearable antennas used for early breast cancer detection. Modeling and performances evaluation of the proposed antenna in terms of return loss, voltage standing wave ratio, radiation pattern, and current distribution have been carried out using CST-MW STUDIO simulator.

A Wireless Sensor Network (WSN) is composed of sensor equipped devices that aim at sensing and processing information from the surrounding environment. Energy consumption is the major concern of WSNs. At the same time, quality of service is to be considered especially when dealing with critical WSNs.In this paper, we present a game theory based approach to maximize quality of service, defined as the aggregate frame success rate, while optimizing power allocation. Game theory is designed to study interactions between players (e.g. chess players) who decide on a set of actions (e.g. the players moves) to reach the objective outcomes (e.g. to win the game). Here, we model the system as a potential game. We show that the optimal power allocation, crucial in a heterogeneous sensor network, is a Nash equilibrium of this game, and we discuss its uniqueness. For simulations, we present a fully distributed algorithm that drives the whole system to the optimal power allocation.

Traffic congestion is a worldwide problem which challenges both scientific community and governments. This paper proposes a novel cost-effective approach which aims to predict congestion levels of road segments and thus helps preventing high traffic congestions. Unlike other approaches based on cooperative vehicular communication, this work adopts a cooperation-without-communication approach inspired by social insects. In fact, vehicles cooperate and share their experiences through RSU (Road Side Unit) controllers placed in the traffic lights of the studied area. Each vehicle is equipped with a navigation device which notifies the driver about congestion levels of road segments. Hence, vehicles’ distribution over the road network tends towards homogeneity. An evolutionary algorithm which optimizes traffic reports exchange between vehicles and RSU controllers is described.

Cloud computing is a set of processes in which a large group of remote servers communicating together so as to allow sharing data-processing tasks, data storage and online access to compute resources. Managing the drastically increasing number of requests presents the most challenging part of cloud computing. This paper discusses a novel hierarchy for optimizing load to achieve a high user satisfaction. By preserving data about the best cloud service providers, this hierarchy enhances the end user’s satisfaction. In other words, as it is proposed in this hierarchy, suppliers with a maximum number of satisfied requests are more likely to be selected as soon as they have available resources/services. On the other hand, when no provider is capable to accomplish the requested tasks, a possibility of cooperation between two or more cloud suppliers is presented as a second option to ensure 100% of user’s satisfaction. In order to apply such an approach, a huge amount of resources are wasted when the in-between communication is taking place. Therefore, an optimized method of SLA contract establishment is tackled in this paper.

In this article, we develop an Active Queue Management (AQM) mechanism for optimizing data traffic within the router, initially, we determine a linear model of TCP network around the operating point, secondly, based on a geometric method and taking into account the communication delay, we synthesize a state feedback controller acting on the probability of packet loss. Finally, we test the validity of our approach through simulations.

In this paper we present a new approach to admission control of new flows in communications networks. Initially, we introduce a traffic classification procedure based on a new construction approach of conservative multiplicative cascades, to ensure information security by blocking malicious attempts and creating priorities over well-intentioned traffic. The admission control process accepts or rejects then the request for a new call by evaluating the available bandwidth within a particular transmission interval for different pre-classified traffic types. The experimental investigation by simulation showed that the proposed method is capable of ensuring the efficient use of available network resources and at the same time providing consistent QoS provisions and data security for network traffic flows.

A mobile ad hoc network (MANET) is a decentralized type of wireless network, characterized by a dynamic topology. Supporting appropriate quality of service for mobile ad hoc networks is a complex and difficult task because of the bandwidth constraints and dynamic nature of the network. A routing protocol has a significant role in terms of the performance. It is used to discover and to establish correct and efficient route between a pair of source and destination nodes so that messages may be delivered in a timely manner. In this paper we have done the study of OLSR (Optimized Link State Routing) protocol. The key concept used in the protocol is that of multi-point relays (MPRs), which are selected nodes that forward broadcast messages during the flooding process. The objective of this paper is to examine QoS constraint in OLSR protocol. We present a state-of-the-art review and a comparison of typical representatives OLSR extensions, designed to enhance the quality of service in the original OLSR. The report aims to create a taxonomy of OLSR extension’s with QoS support on the basis of the nature and the number of the metrics used to adapt the protocol to QoS requirements.

Delay and Disruptive Tolerant Networks (DTNs) is a concept related to environments characterized by very long delay paths and frequent network disruptions. DTN is nowadays a recognized area in networking and communications research, due to its suitability and practical experiences with mobile ad-hoc networks especially in situations where continuous end-to-end paths may not be always guaranteed. In DTNs, nodes store carry and forward messages, called bundles, to other nodes. The forwarding mechanism can occur opportunistically. However, some nodes may show some selfish or malicious behavior, which leads to less cooperation in the network. Thus, one of the main challenges in DTN is to ensure the security and confidentiality within the Network and assure cooperation among nodes. In this paper, we classify some of the threats that have been considered and treated by researchers in the field of DTN, and we propose a new classification based on the degree of cooperation of nodes. We describe different incentive mechanisms used to enhance cooperation among nodes in DTN environment focusing on the strengths of these mechanisms and also their limitations and drawbacks.

The study of routing protocols in wireless sensor networks has been addressed to improve the usage of limited network resources. In this paper, we give in detailed survey of flat routing protocols (flooding, data centric and forwarding) based on network structure in wireless sensor networks, while providing the advantages and disadvantages of each routing protocol. By taking into account several parameters, some of routing protocols in this category will be compared. This paper also highlights the associated problem and application type designated for each protocol.

This paper describes a new approach to build energy aware clusters for Wireless Sensor Networks (WSN). The algorithm behind is based on the k-means method which is well known as a clustering technique and widely used in several fields of engineering and research. K-means clustering tends to find clusters of comparable spatial extent (density clustering). We try to enhance the clustering process by selecting nodes as clusters that are centric and have a high level of energy. This will give the same QoS results as given by the K-means approach with a reduction of energy consumption and a prolongation of the lifetime of the sensor network. For the simulation purposes, we have implemented our approach on the OLSR routing protocol which has been selected by our research team as a test bed routing protocol. We have compared our new approach (OLSR-Kmeans-Energy) with a previous work we developed and where we use a Max-Min heuristic (OLSR-MaxMin-Energy) to enhance QoS parameters and the lifetime of the WSN. Our new approach seems to give better results than the MaxMin approach.

Wireless sensor network represents a new perspective for many applications, including security and surveillance, control, actuation and maintenance of complex systems and fine-grain monitoring of indoor and outdoor environments. However, due to limited resources of sensors and hostile environments in which they could be deployed, this type of networks is vulnerable to several types of attacks similar to those occurring in ad hoc networks. Therefore, it is necessary to use effective mechanisms to protect this type of network. Cryptography can play an important role in detecting and preventing security attacks. Our contribution is intended for applications using the WSN nodes with low mobility and require a high level of security. Unlike most methods in the literature for specific topologies, our security scheme can cover both the needs of flat and hierarchical topologies. In this paper, we proposed a new lightweight cryptography algorithm based on LEAP+. Simulations results of the proposed model are presented using TOSSIM simulator and the complexity of the protocol is analyzed and compared with other symmetric schemes.

This work is directed toward a conception of a computer aid diagnosis (CAD) system to detect suspicious area in digital mammogram and classify them into normal and abnormal. Original image is preprocessed to separate the breast region from it’s background with pectoral muscle suppression to reduce false positive rate.The suspicious regions are extracted using a modified SUSAN algorithm, followed by a function that extract dense regions, then an hierarchical watershed transforms applied to detect edges of suspicious regions.For detected edges Fourier Descriptors are computed and stored as feature vector. A support vector machine is used to classify suspicious regions into normal or abnormal. The proposed system is tested on Mini-Mias database.

Today, mass production multimedia is observed with high variability of form and content, which complicates the management of databases. The use the research techniques based on content has become increasingly necessary rather than the metadata, such as keywords, tags, or descriptions associated with the image. To dynamically associate the most appropriate search technic to each type of image, an intelligent system is required. However, it is very difficult to determine the adequate descriptor and distance for the analysis of a given image, the system quickly becomes unstable. In this paper we develop an application for the implementation and test of the most classic color and texture descriptors, in order to combine them using Entropy Impurity and Mutation approach. Our objective is to increase system performance and stability.Our application is based on a web interface, able to perform an experimental comparison of several methods used in image retrieval, in terms of accuracy and relevance of texture and color descriptors. Distances, between different descriptors are also calculated for four references of multimedia databases.

This paper focuses on producing accurate segmentation of a set of images at different scales. In the process of image co-segmentation, we turn our attention to the task of computing dense correspondences between a set of images. These correspondences are calculated in a dense grid of pixels, where each pixel is represented by an invariant descriptor computed at a unique, manually selected scale, this scale selection limits the efficiency of image co-segmentation methods when the common foregrounds appear at different scales. In this work, we use scale propagation to compute dense correspondences between images by assuming that if two images are being matched, scales should be assigned by considering feature point detections common to both images. We present both quantitative and qualitative tests, demonstrating significant improvements to segment images with large scale variation.

ART (Angular Radial Transform) are widely used in many applications of domains of image processing and pattern recognition, this last is a region based shape descriptor adopted in MPEG-7; among the property, that descriptor is invariant to rotation. The direct computation of ART coefficients characterized by the basis function, which is defined in polar coordinates over a unit disk and digital images are usually defined in cartesian coordinates, which produces two types of errors namely geometric error and integral approximation error and invariant to rotation of ART is not verified. In this paper, we propose an algorithm to compute the coefficients in polar coordinates systems to eliminate these errors, which have been produced by the conventional method. We use cubic interpolation for generation of the pixel to system Polar image, the results show that the proposed approach improves the polar rotation invariance. In order to apply this approach at the gray level and the binary images, which we can compare the time of execution of this last.

In this paper, a novel method for image interpolation is proposed. This method is based on the application of the Laplacian operator for the purpose of detecting the edge-directions and then interpolating the missing pixels using the cubic convolution. We start applying a down-sampled by a factor of two to the gray high-resolution image in order to obtain a low-resolution image. Then, the preprocessed image is reconstructed by using the proposed interpolation method. The proposed method is implemented and tested over several gray images, and also compared to many interpolation methods in the state-of-the-art. The simulation results are shown to be superior compared to the other interpolation methods in both of objective measurement in terms of PSNR, SSIM and FSIM, and visual quality of image results.

In this work, a new method is presented for the representation of 3D objects with binary matrix. This method is based on two steps: normalization and quantization. This representation allows us to compare 3D objects by computing the similarity between them.

To deploy the enormous hardware resources available in Multi-Processor Systems-on-Chip (MPSoC) efficiently, rapidly and accurately, methods of Design Space Exploration (DSE) are needed to evaluate several design choices. In this article, we provide a framework that makes fast simulation and performance evaluation of MPSoC early in flow of design, therefore reducing the time of design. In this platform and within the Transaction Level Modeling (TLM) approach, we present a new definition of ISS level by introducing two complementary modeling ISST and ISSPT sublevels. This later, that we illustrate an arbiter modeling approach that allows a high performance MPSoC communication. A round-robin method is chosen for algorithm arbiter modeling because it is simple, minimizes the communication latency and has an accepted speed-up. Two applications are tested and used to validate our platform: Game of life and JPEG Encoder.The performance of the proposed approach has been analyzed in MPSoC platform based on multi-MicroBlaze. Results of simulation show with ISSPT sublevels gives a high simulation speedup factor of up to 32 with a negligible performance estimation error margin.

Recently, Unmanned Aerial Vehicles (UAV) become a significant research area due to their multiple domains of applications such as: search and rescue operations, aerial surveying of crops, inspecting power lines and pipelines, delivering medical supplies to remote or otherwise inaccessible regions. However the UAV performances (such as autonomy, endurance, maximum flight altitude, maximum takeoff weight, maximum speed etc) depend mainly on its energy storage system (batteries, fuel cells, ultra capacitors). The more the drone’s complexity grows the more energy it consumes. In this paper we will discuss the different electrical architecture used in UAV and we’ll propose a hybrid solution that optimizes the energy consumption for multi-rotor.

Current work in the field related to the drones mainly aimed at improving their autonomy related to the environment. The purpose of this paper focuses on the areas of improvement of autonomy, flexibility and adaptability of these aircraft during a flight. The developing of flying machines characterized by a pseudo-autonomy, better flexibility and adaptability to situations are mainly blocked by order constraints equipment, such as for architecture requires more complexity. To meet this need autonomous control architecture has been developed; it supports various aspects of the development process of the agent, from the design of the agent architecture, to the implementation on the hardware. An original architecture has been developed that allows the real-time control and manage different decisions by evaluating the path to follow and the speed of the UAV (unmanned aerial vehicle). It is deployed on an embedded system platform that provides good computing power for this kind of tasks in addition to managing communication with the ground operator.

Variable-speed wind energy conversion systems (WECSs) have become increasingly important in recent years as they enable obtainment of maximal output power in the fields of the low and average wind speeds. In this study, we focus on WECS using doubly-fed induction generators (DFIGs) and present models for the turbine and doubly-fed induction generator. The main objective is to study two types of nonlinear controls; sliding mode and backstepping used for control of the grid-side converter will be also studied and analyzed. Matlab / Simulink simulation results are included.

Smart Cities are a future reality that emerged recently. They became a wide research field around the world. These cities will combine the power of ubiquitous communication networks and wireless sensors with the efficient management systems to solve daily challenges and create exciting services. In this work, we involve the power of artificial intelligence to solve one of the serious challenges in big cities. This concerns the traffic management and prediction. This work proposes a statistical model serving the analysis of a random graph that represents, in reality, roads on map. Using those models and collected data from sensors or human agents, we can extract useful hidden knowledge for the best decision making. To prove the reliability of the approach, a Monte Carlo simulation algorithm is designed and results confirms the added-value of the approach.

While people are away from their regular social terrain, they are usually exposed to newer situations, where they often need to seek for information or help. Nowadays people can find information from the Internet by using smartphones even when they are traveling. However, for many real–life questions, the Internet is not a suitable source of a ‘reliable answer,’ especially when the information–need or the question is too context–sensitive. Furthermore, it is also difficult to compose a context–sensitive real–life question effectively to find suitable answers. Therefore, along with other reasons, such as, individual’s ability or experience, people seek for help or assistance from other people. And most of the cases, they need personalized support which is tailored for a particular context.With the recent growth of computer mediated online social networks, people can relatively easily ask their social peers for help. However, these networks are not yet suitable for composing questions with rich–media (e.g., with audio) and with contextual information. Aspects of a question (e.g., timeliness, demand for details) become much clearer when the context in which a question being asked is exchanged. In order to address this, a Social Computing system called Just in Time has been developed which is a context and social aware ‘question–and–answer’ system. It utilizes the users’ context and social network to formulate a question. It helps the users to get answers from trustable social peers. A formative evaluation was conducted with a small number of users that used the system for two days. Some interesting side effects were observed, such as, users started using the system as a context–aware ‘instant messaging’ system. It showed that there is a clear benefit in sharing context in order to get relevant answers. And the result was inspiring for further development of social computing research works.

This work is registered in two disciplinary axes that are the decision making system, and the practices of the IT GRC. Many organizations deployed integrated the practices of the IT GRC, the problem that arises it is how to choose the good one practices to satisfy a precise need. Our work is motivated by the need to make decisions by understanding and by incorporating perceptions, decisions and actions to make the best choice. The objective of the research is to build a decision-making model to satisfy a precise need IT. The proposed approach bases on three main stages to set up a decision-making model. The model takes in entrance the strategic needs, the first stage consists in reducing the size of the problem by dividing it into many problems, by basing itself on the mapping between all the reference tables and methods of the GRC and also this stage is going to allow us to assure the sequencing of these under problems according to the variables of the environment as for example the type of the organization. In the second stage, it is a question of formalizing every under problems according to the criteria stored in the datawarehouse to generate the best choice of the good practice by using methods of aggregation multi criterion to satisfy the need IT. The third stage consists in estimating the satisfaction IT and helps to make decisions at the level of every chosen reference table.

Agents in open distributed systems rely on their peers to achieve their goals. In such situation, the trust management become a critical subject that must be handled. Formalizing trust as a computer concept will help agents improving the decision making process and decrease the risk of being unsatisfied. This research aims to develop a practical framework that introduce computational trust models in multi-agent systems applications. The framework presented in this paper is based on an abstract structure that handle different trust models, and provide a ready to use development tool for JADE applications.

In the context of IT governance, different companies are using their expertise to come out with a new solution that helps their own governance. In fact, information systems managers struggle to comply with laws and regulations applied by their companies countries. With the variety of tools and frameworks, they need to know all processes in order to apply the only process that is going to be of help to their systems. In our case, we choose to discuss and study IT risk management which constitute an important component of the IT-GRC architecture. We have published several papers in this subject and we are still enhancing different aspects of the EAS-SGR architecture. In this paper, we will demonstrate the several interconnexions between IT-GRC components. These systems are based on multi-agent and expert systems knowing their integrated artificial intelligence. This expertise is one of our primal elements that were never used before in scientific research.

Enterprise architecture (EA) is a business and IT management tool that has grown in popularity during the last decade. It is based on models of business and IT with systematic frameworks. This paper provides an interesting overview on the agility measurement and dimensions. The proposed approach precises the components of each enterprise architecture layers and the complexity of the future architecture.

Over recent years, The progress made in best practices and the popularity of enterprise architecture systems have grown to give rise to new applications called Tools of Urbanization for Information Systems. The current information systems must adapt to these new environments by providing a transparent access to both information and services by using intelligent systems. The major challenge of these tools is to adapt to new market framework and to have strategies allowing them dynamically in the application.In this paper, we will develop the mecanism of adaptation of framework in enterprise architecture and define the politic of change for the implementation of the new practices in Information System.Our approach uses multi-agent systems to give the changes plan in order to implement the new IT governance framework.

PMBOK (project management body of knowledge) is the recognized and the most accepted standard for project management, however many projects still fail by using or misusing PMBOK guidelines, due to poor communications, lack of monitoring and non performance measurement. In this paper we use the advantages of agent technology to make implementation and use of PMBOK processes more efficient and to have insights on the progress of projects and to anticipate possible problems that can lead the project failure.