Cybersecurity issues in wireless sensor networks: current challenges and solutions - Djallel Eddine Boubiche; Samir Athmani; Sabrina Boubiche; Homero Toral-Cruz (Wireless Personal Communications, 2021)

Discrete Large-scale Multi-Objective Teaching-Learning-Based Optimization Algorithm - Aouadj, Wafa; Abdessemed, Mohamed Rida; Rachid Seghir (Proceedings of the 4th International Conference on Networking, Information Systems & Security, 2021)

An Efficient Approach for Big Data Aggregation Mechanism in Heterogeneous Wireless Connected Sensor Networks - Sabrina Boubiche; Azeddine Bilami; Djallel Eddine Boubiche (Wireless Personal Communications, 2021)

Fine-tuned Xception for Image Classification on Tiny ImageNet - Benbrahim, Hayet; Ali Behloul (2021 International Conference on Artificial Intelligence for Cyber Security Systems and Privacy (AI-CSP), 2021)

A framework for spectrum harvesting in heterogeneous wireless networks integration - Samir Gourdache; Azeddine Bilami; Kamel Barka (Journal of King Saud University-Computer and Information Sciences, 2021)

Heuristically accelerated reinforcement learning for channel assignment in wireless sensor networks - Sahraoui, Mohamed; Azeddine Bilami; Taleb-Ahmed, Abdelmalik (International Journal of Sensor Networks, 2021)

An Incremental Model Projection Applied to Streamline Software Architecture Assessment and Monitoring - Kadri, Salim; Aouag, Sofiane; Djalal Hedjazi (International Journal of Information System Modeling and Design (IJISMD), 2021)

Industrial IoT middleware using a multi-agent system for consistency-based diagnostic in cement factory - Ayoub Benayache; Azeddine Bilami; Benaggoune, Khaled; Hayet Mouss (International Journal of Autonomous and Adaptive Communications Systems, 2021)

MS-QuAAF: A generic evaluation framework for monitoring software architecture quality - Kadri, Salim; Aouag, Sofiane; Djalal Hedjazi (Information and Software Technology, 2021)

A parallel content-based image retrieval system using spark and tachyon frameworks - Saliha Mezzoudj; Ali Behloul; Rachid Seghir; Yassmina Saadna (Journal of King Saud University-Computer and Information Sciences, 2021)

A policy-based solution for the detection of colluding GPS-Spoofing attacks in FANETs - Bada, Mousaab; Djallel Eddine Boubiche; Lagraa, Nasreddine; Kerrache, Chaker Abdelaziz; Muhammad Imran; Muhammad Shoaib (Transportation Research Part A: Policy and Practice, 2021)

A Privacy-Preserving Authentication Model Based on Anonymous Certificates in IoT - Khaled Hamouid; Omar, Mawloud; Kamel Adi (2021 Wireless Days (WD), 2021)

Robust and Accurate Method for Textual Information Extraction Over Video Frames - Belkacem, Soundes; Larbi Guezouli (Advances on Smart and Soft Computing, 2021)

Securing human‐to‐thing interactions in the Internet of Things with asymmetric and selective mechanism - Somia Sahraoui; Azeddine Bilami (Security and Privacy, 2021)

A set of statistical radial binary patterns for tree species identification based on bark images - Boudra, Safia; Yahiaoui, Itheri; Ali Behloul (Multimedia Tools and Applications, 2021)

Towards a non monotonic agent testing - Douha, Djamel; Mokhtari, Aicha; Guessoum, Zahia; Mandiau, René (2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA), 2021)

Towards a non monotonic agent testing, reasoning about messages and behavior - Douha, Djamel; Mokhtari, Aicha; Guessoum, Zahia (8th ACS/IEEE International Conference on Computer Systems and Applications AICCSA 2021, 2021)

A parallel content-based image retrieval system using spark and tachyon frameworks - Saliha Mezzoudj; Ali Behloul; Rachid Seghir; Yassmina Saadna (Journal of King Saud University - Computer and Information Sciences, 2021)
With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps. (i) image indexation step, in which we use MapReduce distributed model on Spark in order to speed up the indexation process. We also use a memory-centric distributed storage system, called Tachyon, to enhance the write operation (ii) image retrieving step which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on MapReduce model implemented under Apache Spark, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.

CARTEE: congestion avoidance with reliable transport and energy efficiency for multimedia applications in wireless sensor networks - Abderrezak Benyahia; Azeddine Bilami; Maamar Sedrati (Wireless Networks, 2020)

A Clinical Reasoning Learning Groupware: An exploratory study of factors affecting the adoption behavior - Djalal Hedjazi; Chorfi, Atef; Aouag, Sofiane (2020 4th International Symposium on Informatics and its Applications (ISIA), 2020)

A Cross-Layer Fault Tolerant Protocol with Recovery Mechanism for Clustered Sensor Networks - Yasmine Djebaili; Azeddine Bilami (Sensor Technology: Concepts, Methodologies, Tools, and Applications, 2020)

A Distributed Information Retrieval Approach for Copyright Protection - Benbelgacem, Sonia; Larbi Guezouli; Rachid Seghir (Proceedings of the 3rd International Conference on Networking, Information Systems & Security, 2020)

Face Recognition Based on Harris Detector and Convolutional Neural Networks - Zeghina, Assaad Oussama; Zoubia, Oussama; Ali Behloul (International Symposium on Modelling and Implementation of Complex Systems, 2020)

Impact of Mobility Models on Energy Consumption in Unmanned Aerial Ad-Hoc Network - Bensalem, Amina; Djallel Eddine Boubiche; Zhou, Fen; Rachedi, Abderrezak; Mellouk, Abdelhamid (2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020)

An IoT-Based Adaptive Traffic Light Control Algorithm for Isolated Intersection - Haddad, Tarek Amine; Djalal Hedjazi; Aouag, Sofiane (International Conference on Computing Systems and Applications, 2020)

LSTR: lightweight and secure tree-based routing for wireless sensor networks - Khaled Hamouid; Othmen, Salwa; Barkat, Amine (Wireless Personal Communications, 2020)

Mobility Based Genetic Algorithm for Heterogeneous Wireless Networks - Kamel Barka; Lyamine Guezouli; Samir Gourdache; Ameghchouche, Sara (International Conference on Machine Learning for Networking, 2020)

Multi-view model-driven projection to facilitate the control of the evolution and quality of the architecture - Kadri, Salim; Aouag, Sofiane; Djalal Hedjazi (International Journal of Software Innovation (IJSI), 2020)

A New Mobile Collaborative Approach Based Relays for Wireless Sensor Networks - Lyamine, Guezouli; Kamel, Barka; Souheila, Bouam (International Journal of Information Science and Technology, 2020)

Privacy-aware Authentication Scheme for Electric Vehicle In-motion Wireless Charging - Khaled Hamouid; Kamel Adi (2020 International Symposium on Networks, Computers and Communications (ISNCC), 2020)

Problem-based collaborative learning groupware to improve computer programming skills - Chorfi, Atef; Djalal Hedjazi; Aouag, Sofiane; Djallel Eddine Boubiche (Behaviour & Information Technology, 2020)

Static versus dynamic memory allocation: a comparison for linear algebra kernels - Toufik Baroudi; Vincent Loechner; Rachid Seghir (IMPACT 2020, in conjunction with HiPEAC 2020, 2020)

Towards architectural view-driven modernization - Aouag, Sofiane; Kadri, Salim; Djalal Hedjazi (2020 International Conference on Advanced Aspects of Software Engineering (ICAASE), 2020)

UAVs's efficient controlled mobility management for mobile heterogeneous wireless sensor networks - Lyamine Guezouli; Kamel Barka; Djehiche, Asma (Journal of King Saud University-Computer and Information Sciences, 2020)

Multi-level approach for controlling architecture quality with Alloy - Kadri, Salim; Aouag, Sofiane; Djalal Hedjazi (2019 International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), 2019)

Security for internet of things: A state of the art on existing protocols and open research issues - Mahmoud, Chaira; Aouag, Sofiane (Proceedings of the 9th international conference on information systems and technologies, 2019)

Proposal of a new self-organizing protocol for data collection regarding Mobile Wireless Sensor and actor Networks - Kamel Barka; Lyamine Guezouli; Samir Gourdache; Djallel Eddine Boubiche (2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019)
Mobile Wireless Sensor and Actor Networks (MWSANs) can simply be defined as an extension of Wireless Sensor and Actor Networks (WSANs) in which the actor nodes are mobile. As such, in addition to challenges existing in WSAN, the mobility also imposes new challenges such as localization of actors, cooperative tracking of both actor-actor and actor-sensor collaboration, and communication infrastructure between distant actors. New communication protocols, specific to MWSANs, are needed. In this paper, we propose a self-organization and data collection protocol in order to provide energy efficiency, low latency, high success rate and suitably interactions between sensors and actors and take benefit from the mobility and resources existing on the network's actor nodes. The actor nodes move according to RWP mobility model. Each actor, during its pause time creates a temporary cluster, and is the head of it, collects and processes sensor data and performs actions on the environment based on the information gathered from sensor nodes in its cluster. Once an actor detects a base station it delivers the collected data to it. The simulations carried out (with TOSSIM tool), comfort us with good performances results.

Self-organization Smart Protocol for Mobile Wireless Sensor Networks - Lyamine Guezouli; Kamel Barka; Samir Gourdache; Djallel Eddine Boubiche (2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019)
In this paper, we propose a novel self-organization protocol for wireless sensor networks (WSNs) assisted by Unmanned Aerial Vehicle (UAV or Drone) called SSP (Self-organization Smart Protocol). In order to provide energy efficiency, low latency, high success rate and suitably interactions between sensors and UAVs while taking advantage of the air mobility (fly) and resource available on the UAVs in the network. The UAVs move according to RWP (Random Waypoint) mobility model. Each UAV, during its pause time at a known height, creates a temporary cluster, and acts as its head, collects and processes sensor data and performs actions on the environment based on the information gathered from sensor nodes in its cluster. Once an UAV detects a base station (BS) it forwards the collected data to it. The results of the simulations show the high performance of the proposed algorithm.

Pseudo Zernike moments-based approach for text detection and localisation from lecture videos - Belkacem Soundes; Guezouli Larbi; Zidat Samir (International Journal of Computational Science and Engineering, 2019)
Scene text presents challenging characteristics mainly related to acquisition circumstances and environmental changes resulting in low quality videos. In this paper, we present a scene text detection algorithm based on pseudo Zernike moments (PZMs) and stroke features from low resolution lecture videos. Algorithm mainly consists of three steps: slide detection, text detection and segmentation and non-text filtering. In lecture videos, slide region is a key object carrying almost all important information; hence slide region has to be extracted and segmented from other scene objects considered as background for later processing. Slide region detection and segmentation is done by applying pseudo Zernike moment's based on RGB frames. Text detection and extraction is performed using PZMs segmentation over V channel of HSV colour space, and then stroke feature is used to filter out non-text region and to remove false positives. The algorithm is robust to illumination, low resolution and uneven luminance from compressed videos. Effectiveness of PZM description leads to very few false positives comparing to other approached. Moreover resulting images can be used directly by OCR engines and no more processing is needed.

A parallel content-based image retrieval system using spark and tachyon frameworks - Saliha Mezzoudj; Ali Behloul; Rachid Seghir; Yassmina Saadna (Journal of King Saud University - Computer and Information Sciences, 2019)
With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps. (i) image indexation step, in which we use MapReduce distributed model on Spark in order to speed up the indexation process. We also use a memory-centric distributed storage system, called Tachyon, to enhance the write operation (ii) image retrieving step which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on MapReduce model implemented under Apache Spark, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.

Secure and reliable certification management scheme for large-scale MANETs based on a distributed anonymous authority - Khaled Hamouid; Kamel Adi (Peer-to-Peer Networking and Applications, 2019)
This paper proposes a compromise-tolerant (t,n)-threshold certification management scheme for MANETs. Our solution allows to mitigate the impact of compromised nodes that participate in the certification service. In our design, certification management is achieved anonymously by an Anonymous Certification Authority (ACA). The latter is fully distributed into multiple disjointed coalitions of nodes whose structure is made hidden. This prevents an adversary from taking the control of the ACA by arbitrarily compromising t or more nodes. In other words, our proposal enhances the compromise-tolerance to more than the threshold number t of nodes without breaking down the whole certification system. As a result, our scheme requires a very smaller threshold than traditional schemes, which improves considerably the service availability. The experimental study shows a clear advantage over traditional threshold-based certification schemes by ensuring a significant positive compromise between security and availability of certification service.

A Bayer pattern-based fragile watermarking scheme for color image tamper detection and restoration - Wassila Belferdi; Ali Behloul; Lemnouar Noui (Multidimensional Systems and Signal Processing, 2019)
The security of multimedia documents becomes an urgent need, especially with the increasing image falsifications provided by the easy access and use of image manipulation tools. Hence, usage of image authentication techniques fulfills this need. In this paper, we propose an effective self-embedding fragile watermarking scheme for color images tamper detection and restoration. To decrease the capacity of insertion, a Bayer pattern is used to reduce the color host image into a gray-level watermark, to further improve the security Torus Automorphism permutation is used to scramble the gray-level watermark. In our algorithm, three copies of the watermark are inserted over three components (R, G, and B channels) of the color host image, providing a high probability of detection accuracy and recovery if one copy is destroyed. In the tamper detection process, a majority voting technique is used to determine the legitimacy of the image and recover the tampered regions after interpolating the extracted gray-level watermark. Using our proposed method, tampering rate can achieve 25% with a high visual quality of recovered image and PSNR values greater than 34 (dB). Experimental results demonstrate that the proposed method affords three major properties: the high quality of watermarked image, the sensitive tamper detection and high localization accuracy besides the high-quality of recovered image.

Speed limit sign detection and recognition system using SVM and MNIST datasets - Yassmina Saadna; Ali Behloul; Saliha Mezzoudj (Neural Computing and Applications, 2019)
This article presents a computer vision system for real-time detection and robust recognition of speed limit signs, specially designed for intelligent vehicles. First, a new segmentation method is proposed to segment the image, and the CHT transformation (circle hog transform) is used to detect circles. Then, a new method based on local binary patterns is proposed to filter segmented images in order to reduce false alarms. In the classification phase, a cascading architecture of two linear support vector machines is proposed. The first is trained on the GTSRB dataset to decide whether the detected region is a speed limit sign or not, and the second is trained on the MNIST dataset to recognize the sign numbers. The system achieves a classification recall of 99.81% with a precision of 99.08% on the GTSRB dataset; in addition, the system is also tested on the BTSD and STS datasets, and it achieves a classification recall of 99.39% and 98.82% with a precision of 99.05% and 98.78%, respectively, within a processing time of 11.22 ms.

A Generalized and Parallelized SSIM-Based Multilevel Thresholding Algorithm - Ikram Boubechal; Seghir Rachid; Redha Benzid (Applied Artificial Intelligence, 2019)
Multilevel thresholding is a widely used technique to perform image segmentation. It consists of dividing an input image into several distinct regions by finding the optimal thresholds according to a certain objective function. In this work, we generalize the use of the SSIM quality measure as an objective function to solve the multilevel thresholding problem using empirically tuned swarm intelligence algorithms. The experimental study we have conducted shows that our approach, producing near-exact solutions, is more effective compared to the state-of-the-art methods. Moreover, we show that the computation complexity has been significantly reduced by adopting a shared-memory parallel programming paradigm for all the algorithms we have implemented.

Towards large-scale face-based race classification on spark framework - Mezzoudj Saliha; Behloul Ali; Seghir Rachid (Multimedia Tools and Applications, 2019)
Recently, the identification of an individual race has become an important research topic in face recognition systems, especially in large-scale face images. In this paper, we propose a new large-scale race classification method which combines Local Binary Pattern (LBP) and Logistic Regression (LR) on Spark framework. LBP is used to extract features from facial images, while spark’s logistic regression is used as a classifier to improve the accuracy and speedup the classification system. The race recognition method is performed on Spark framework to process, in a parallel way, a large scale of data. The evaluation of our proposed method has been performed on two large face image datasets CAS-PEAL and Color FERET. Two major races were considered for this work, including Asian and Non-Asian races. As a result, we achieve the highest race classification accuracy (99.99%) compared to Linear SVM, Naive Bayesian (NB), Random Forest(RF), and Decision Tree (DT) Spark’s classifiers. Our method is compared against different state-of-the-art methods on race classification, the obtained results show that our approach is more efficient in terms of accuracy and processing time.

A multi-agent system for distributed maintenance scheduling - Djalal Hedjazi; Fateh Layachi; Djallel Eddine Boubiche (https://www.sciencedirect.com/science/article/pii/S004579061832620X#!, 2019)
Due to the intrinsically geo-distributed subcontracting maintenance activity practice, the maintenance scheduling has for a long time been a major challenge in the industry. This research work presents a methodology to schedule the maintenance activities of geo-distributed assets. A multi-agent system based approach is proposed to enable the decision-making for the subcontractors in a distributed industrial environment under uncertainty. An auction based negotiation mechanism is designed to promote competition and cooperation among the different agents, and to obtain global good schedule.Compared to the Weighted Shortest Processing Time first–Heuristic–Earliest Due Date (WSPT-H-EDD) method, the experimental results show that the proposed approach is able to provide scheduling scheme with good performances in terms of Global Cost, Total Weighted Tardiness Cost and makespan.

A framework for spectrum harvesting in heterogeneous wireless networks integration - Samir Gourdache; Azeddine Bilami; Kamel Barka (Journal of King Saud University - Computer and Information Sciences, 2019)
Today’s, and near future, communication networks rely heavily on capacity expansion to keep pace with the massive number of mobile devices and ever-increasing mobile traffic. This expansion can be achieved through three major ingredients, namely, adding more wireless-spectrum, efficient usage of this spectrum, and adequate networks’ architectures. In this paper, a proposition for integrating these three ingredients in a cognitive-radio-inspired framework is presented. The focus is on the integration of the idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. This framework is based on a conceptual network-architecture articulated with a generic and cooperative spectrum-harvesting scheme. The former brings the necessary agility for such heterogeneous environments, the latter keeps the network supplied with the vital spectrum resources. In our proposal, we make use of cross-correlated sequences (CCSs) for context-aware events’ signaling purposes. This choice is motivated by the particularly interesting characteristics of CCSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

A multi-agent system for distributed maintenance scheduling - Djalal Hedjazi; Fateh Layachi; Djallel Eddine Boubiche (Computers & Electrical Engineering, 2019)
Due to the intrinsically geo-distributed subcontracting maintenance activity practice, the maintenance scheduling has for a long time been a major challenge in the industry. This research work presents a methodology to schedule the maintenance activities of geo-distributed assets. A multi-agent system based approach is proposed to enable the decision-making for the subcontractors in a distributed industrial environment under uncertainty. An auction based negotiation mechanism is designed to promote competition and cooperation among the different agents, and to obtain global good schedule.Compared to the Weighted Shortest Processing Time first–Heuristic–Earliest Due Date (WSPT-H-EDD) method, the experimental results show that the proposed approach is able to provide scheduling scheme with good performances in terms of Global Cost, Total Weighted Tardiness Cost and makespan.

EDAK: An Efficient Dynamic Authentication and Key Management Mechanism for heterogeneous WSNs - Samir Athmani; Azeddine Bilami; Djallel Eddine Boubiche (Future Generation Computer Systems, 2019)
Securing the network communication represents one of the most important challenges in wireless sensor networks. The key distribution problem has been widely discussed in classical wireless sensor networks contrarily to heterogeneous ones. HWSNs (Heterogeneous Wireless Sensor Networks) have optimized the network capability and opened new security opportunities by introducing high resource capacity sensor nodes in the network. In this paper, an efficient dynamic authentication and key Management scheme is proposed for heterogeneous WSN. The main idea is to provide a single lightweight protocol for both authentication and key establishment while optimizing the security level. The key distribution algorithm is based on preexisting information to generate dynamic keys and does not require any secure channel and sharing phase which improves the security, energy efficiency and reduces the memory consumption. Experimental results have confirmed the performances of our mechanism compared to some of the existing security protocols.

MsM: A microservice middleware for smart WSN-based IoT application - Ayoub Benayache; Azeddine Bilami; Sami Barkat; Pascal Lorenz; Hafnaoui Taleb (Journal of Network and Computer Applications, 2019)
Actually, wireless sensor networks represent a substantial part in IoT. However, their limitation requires a special consideration in IoT applications. For their integration with the internet, it is necessary to adapt such networks using different middleware, with taking into account various challenges such as heterogeneity and interoperability. Previously Service Oriented Architecture (SOA) was the suitable design, but with a better practice, a new design called microservice becomes the leader due to its high performance and its suitability for IoT applications. In this paper, we first survey the most important middleware that have been proposed to handle WSN through IoT. Also, we discuss the most crucial microservices that handle different integration factors by making them supported by the proposed middleware. Our proposal is inspired from artificial neural network architecture to allow dynamic service interaction; it supports unlimited services with a regard to various device capabilities separately of the cloud technologies. Moreover, the evaluation of our design clearly shows that our middleware allows a lightweight WSN integration with IoT regarding to their limitations and requirements.

A Novel Method for Polar Form of Any Degree of Multivariate Polynomials with Applications in IoT - Sedat Akleylek; Meryem Soysaldı; Djallel Eddine Boubiche; Homero Toral-Cruz (Sensors (Basel), 2019)
Identification schemes based on multivariate polynomials have been receiving attraction in different areas due to the quantum secure property. Identification is one of the most important elements for the IoT to achieve communication between objects, gather and share information with each other. Thus, identification schemes which are post-quantum secure are significant for Internet-of-Things (IoT) devices. Various polar forms of multivariate quadratic and cubic polynomial systems have been proposed for these identification schemes. There is a need to define polar form for multivariate dth degree polynomials, where d ≥ 4 . In this paper, we propose a solution to this need by defining constructions for multivariate polynomials of degree d ≥ 4 . We give a generic framework to construct the identification scheme for IoT and RFID applications. In addition, we compare identification schemes and curve-based cryptoGPS which is currently used in RFID applications.

Mobile crowd sensing – Taxonomy, applications, challenges, and solutions - Djallel Eddine Boubiche; Muhammad Imran; Aneela Maqsood; Muhammad Shoaib (Computers in Human Behavior, 2019)
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions.

A variant of random way point mobility model to improve routing in wireless sensor networks - Lyamine Guezouli; Kamel Barka; Souheila Bouam; Abdelmadjid Zidani (International Journal of Information and Communication Technology, 2018)
The mobility of nodes in a wireless sensor network is a factor affecting the quality of service offered by this network. We think that the mobility of the nodes presents an opportunity where the nodes move in an appropriate manner. Therefore, the routing algorithms can benefit from this opportunity. Studying a model of mobility and adapt it to ensure an optimal routing in an agitated network is the purpose of our work. We are interested in applying a variant of the mobility model RWP (named routing-random waypoint 'R-RWP') on the whole network in order to maximise the coverage radius of the base station (which will be fixed in our study) and thus to optimise the data delivery end-to-end delay.

Constructing collective competence: a new CSCW-based approach - Djalal Hedjazi (International Journal of Information and Communication Technology, 2018)
Within the majority of contexts, it is persons that are considered to be competent or incompetent. However, in many cases it is the performance of groups and teams that is most important. This implies a concept of collective competence that integrates the set of skills in a group. In addition, the collective competence construction process is also enriched through collaboration which implies exchanges, confrontations, negotiations and interpersonal interactions. This paper presents our CSCW-based approach supporting collective competence construction. As a case of study, the industrial maintenance workspace is fundamentally a collaborative context. Our contribution in this area led us first, to analyse the related task in order to highlight collaborative maintenance vital needs and design the appropriate required group awareness supports which will be used to support collective competence. Finally, the experimentation study identifies the highly effective group awareness tools.

Sensor-based wearable system for the detection and automatic treatment of nocturnal hypoglycaemia - Somia Sahraoui; Sofiane Sahraoui; Oussama Benbousa; Ahmed-Sami Berkani; Azeddine Bilami (Healthcare Technology Letters, 2018)
Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient's blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

A Cross-Layer Fault Tolerant Protocol with Recovery Mechanism for Clustered Sensor Networks - Yasmine Djebaili; Azeddine Bilami (International Journal of Distributed Systems and Technologies (IJDST), 2018)
This article describes how fault tolerance is an essential issue for many WSN (Wireless Sensor Network) applications such as wildlife monitoring, battlefield surveillance and health monitoring. It represents a great challenge for researchers regarding to the characteristics of sensor nodes which are prone to failures due essentially to their limited resources. Faults may occur, not only when sensor nodes exhaust their energy, but also when the congestion phenomenon emerges, because of a high traffic in the network and limited storage capacity of the sensor nodes. In order to support fault tolerance in WSNs, the authors propose a new scheme which incorporates a link quality estimation algorithm and a congestion detection mechanism to enable nodes that present high quality links to be chosen for routing in a non-congested area in case of faults. Evaluations through simulations under NS2 show that our proposed protocol tolerates faults with a minimum cost relatively to HEEP protocol and improves network's performances comparatively to other fault tolerant protocols such as EF-LEACH.

A fuzzy trust-based routing model for mitigating the misbehaving nodes in mobile ad hoc networks - Abdesselem Beghriche; Azeddine Bilami (International Journal of Intelligent Computing and Cybernetics, 2018)
Security is one of the major challenges in the design and implementation of protocols for mobile ad hoc networks (MANETs). In such systems, the cooperation between nodes is one of the important principles being followed in the current research works to formulate various security protocols. Many existing works assume that mobile nodes will follow prescribed protocols without deviation. However, this is not always the case, because these networks are subjected to a variety of malicious attacks. Since there are various models of attack, trust routing scheme can guarantee security and trust of the network. The purpose of this paper is to propose a novel trusted routing model for mitigating attacks in MANETs.

Spectrum harvesting for heterogeneous wireless networks integration - Samir Gourdache; Azeddine Bilami; Kamel Barka (Wireless Networks, 2018)
Massive capacity demand is a major impetus behind the advances, in various ways, of today and near future wireless communication networks. To face this challenge, more wireless spectrum is needed, efficient usage of this spectrum is necessary, and adequate architectures are required. In this paper, we present a conceptual solution based on a cognitive-radio-inspired cellular network, for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. We describe the conceptual architecture of this integrating network, referred to as Integrating cognitive-radio-inspired cellular network (I-CRICNet), and present a cooperative spectrum-harvesting scheme that keeps the former supplied with spectrum resources. In the latter scheme, we make extensive use of cross-correlated sequences (CSSs), for events signaling purposes. This choice is motived by the particularly interesting characteristics of the CSSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

CARTEE: congestion avoidance with reliable transport and energy efficiency for multimedia applications in wireless sensor networks - Abderrezak Benyahia; Azeddine Bilami; Maamar Sedrati (Wireless Networks, 2018)
Reliable data transport is an essential requirement for many multimedia applications in wireless sensor networks. Actually, an efficient transport protocol for these applications must take into account not only reliability and energy consumption factors but also memory occupancy and data delivery delay. Recently, many research works have been conducted in this area, however the proposed protocols treat some of these aspects and neglect others. Contrarily, in this paper we present a novel transport solution designed to provide 100% reliability without making light of other factors. Through different mechanisms, we attempt to reach this objective with congestion avoidance and good performances in terms of energy consumption, delivery delay, and memory storage. The proposed protocol, called congestion avoidance with reliable transmission and energy efficiency (CARTEE), attains these goals through several mechanisms, namely: fixed sliding window transmission, alternative implicit/explicit acknowledgement, a new congestion detection technique, and distributed transmission rate adjustment. To evaluate the proposed protocol, we have conducted simulations using ns-3. The obtained results confirm the efficiency and scalability of CARTEE and demonstrate that it outperforms the recent proposed transport protocols in terms of reliability, congestion avoidance, data cache occupancy, and latency.

A Flocking-Based on Demand Routing Protocol for Unmanned Aerial Vehicles - Nour El Houda Bahloul; Saadi Boudjit; Marwen Abdennebi; Djallel Eddine Boubiche (Journal of Computer Science and Technology, 2018)
The interest shown by some community of researchers to autonomous drones or UAVs (unmanned aerial vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we proposed a flocking-based routing protocol for UAVs called BR-AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. Moreover, an automatic ground base stations discovery mechanism has been introduced for a proactive drones and ground networks association needed for the context of real-time applications. The performance of BR-AODV was evaluated and compared with that of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

Advanced Industrial Wireless Sensor Networks and Intelligent IoT - Djallel-Eddine Boubiche; Al-Sakib Khan Pathan; Jaime Lloret; Huiyu Zhou; Seongik Hong; Syed Obaid Amin; Mohamed Ali Feki (IEEE Communications Magazine, 2018)
Examines the market for wireless sensor networks in the era and expansion of the Internet of Things. Over the past decade, the fast expansion of the Internet of Things (IoT) paradigm and wireless communication technologies has raised many scientific and engineering challenges that call for ingenious research efforts from both academia and industry. The IoT paradigm now covers several technologies beyond RFID and wireless sensor networks (WSNs). In fact, the number of potential application fields has already exceeded expectations. According to Cisco IBSG, more than 50 billion devices are expected to be connected to the Internet by 2020, with around 20 percent from the industry sector. Therefore, integrating the IoT concept and industrial WSNs (IWSNs) is an attractive choice for industrial processes, which may optimize operational efficiency, automation, maintenance, and rationalization. Moreover, IoT ensures large-scale interconnection between machines, computers, and people, enabling intelligent industrial operations. This emergent technological evolution has led to what has become the Industrial IoT (IIoT). IIoT will bring promising opportunities, along with new challenges.

Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks - Sabrina Boubiche; Djallel Eddine Boubiche; Azzedine Bilami; Homero Toral-Cruz (IEEE Access, 2018)
The emergence of new data handling technologies and analytics enabled the organization of big data in processes as an innovative aspect in wireless sensor networks (WSNs). Big data paradigm, combined with WSN technology, involves new challenges that are necessary to resolve in parallel. Data aggregation is a rapidly emerging research area. It represents one of the processing challenges of big sensor networks. This paper introduces the big data paradigm, its main dimensions that represent one of the most challenging concepts, and its principle analytic tools which are more and more introduced in the WSNs technology. The paper also presents the big data challenges that must be overcome to efficiently manipulate the voluminous data, and proposes a new classification of these challenges based on the necessities and the challenges of WSNs. As the big data aggregation challenge represents the center of our interest, this paper surveys its proposed strategies in WSNs.

Modeling collaborative learning: case of clinical reasoning - Mohamed-Abderraouf Ferradji (International conference of E-Health and Medical Communications, 2017)

Towards virtual collaborative learning of clinical skills - Mohamed-Abderraouf Ferradji; Djalal Hedjazi (International Conference on Internet of Things, Embedded Systems and Communications (IINTEC), 2017)

Evaluation of QoS parameters with RPL protocol in the Internet of Things - Sedrati Maamar (Proceedings of the International Conference on Computing for Engineering and Sciences (ICCES '17), 2017)
The objective of this work is to present an analysis of RPL Routing protocol for Low-Power and Lossy Networks (LLNs) in the Internet of Things (IoT) and to determine the adequate working mode between storing and non-storing. Objects in LLNs networks have limited processing power such as battery and memory. The study examined the behavior of RPL towards some number of quality of service parameters in Wireless Sensor Networks (WSNs). Simulations are conducted under ContikiCooja Simulator. Results show that non-storing mode has better results in terms of delay and loss rate, but the storing mode consumes less energy.

Bio-Inspired on Demand Routing Protocol for Unmanned Aerial Vehicles - Nour El Houda Bahloul; Saadi Boudjit; Marwen Abdennebi; Djallel Eddine Boubiche (2017 26th International Conference on Computer Communication and Networks (ICCCN), 2017)
The interest shown by some community of researchers to autonomous drones or UAVs (Unmanned Aerial Vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we have proposed a bio-inspired routing protocol for UAVs called BR- AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. The performances of BR-AODV were evaluated and compared to those of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

In-Body Routing Protocols for Wireless Body Sensor NetworksPublisher: IEEECite ThisPDF - Bendjehich Romaissa; Boubiche Djallel Eddine (2017 10th International Conference on Developments in eSystems Engineering (DeSE), 2017)
Recent advances in wireless communication have led to the introduction of a novel network of miniaturized, low power, intelligent sensors that can be placed in, on, or around the body. This network is referred to as Wireless Body Area Network (WBAN). The main purpose of WBAN is to physiologically monitor patient's vital signs and consequently route the related data towards a base station. Since the environment of such a network is principally the human body, data routing mechanisms used in traditional wireless networks (e.g. WSN, WANET) need to be revised, and more restrictions have to be addressed in order to adapt it to WBAN routing challenges. Compared to those dedicated to on-body WBAN, in-body WBAN routing protocols have more constrains and restrictions and are expected to be efficient and robust. As better as we know, only few routing protocols have been proposed in literature and the research field stills underexplored. Therefore, in this paper we present an overview of the main existing routing protocols proposed for wireless in-body sensor networks (WIBSN).

Integration of energy aware WSNs in cloud computing using NDN approach - Hafnaoui Taleb; Sofiane Hamrioui; Pascal Lorenz; Azzedine Bilami (2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017)
Nowadays, wireless sensor networks (WSNs) are becoming challenging issue and used in many fields and applications. WSNS are characterized by many constraints as low energy, low computation capability and weak transmission range. The cloud computing is promising technology that can provide a flexible storage and processing infrastructure to process WSN's data in large scale. The two technologies (i.e.: WSNs, Cloud Computing) have gained significant research interest and their combining is a fundamental challenge that certainly will resolve many issues related to WSNs. In this paper we discuss firstly the idea of integrating WSNs in Cloud Computing starting with a state of the art analysis of existing approaches in this field. The second part of this paper is devoted to a comparative study between two efficient energy protocols that are proposed for WSNs.

Motion Detection of Some Geometric Shapes in Video Surveillance - Larbi Guezouli; Hanane Belhani (American Journal of Data Mining and Knowledge Discovery, 2017)
Motion detection is a live issue. Moving objects are an important clue for smart video surveillance systems. In this work we try to detect the motion in video surveillance systems. The aim of our work is to propose solutions for the automatic detection of moving objects in real time with a surveillance camera. We are interested by objects that have some geometric shape (circle, ellipse, square, and rectangle). Proposed approaches are based on background subtraction and edge detection. Proposed algorithms mainly consist of three steps: edge detection, extracting objects with some geometric shapes and motion detection of extracted objects.

An overview of traffic sign detection and classification methods - Yassmina Saadna (International Journal of Multimedia Information Retrieval, 2017)
Over the last few years, different traffic sign recognition systems were proposed. The present paper introduces an overview of some recent and efficient methods in the traffic sign detection and classification. Indeed, the main goal of detection methods is localizing regions of interest containing traffic sign, and we divide detection methods into three main categories: color-based (classified according to the color space), shape-based, and learning-based methods (including deep learning). In addition, we also divide classification methods into two categories: learning methods based on hand-crafted features (HOG, LBP, SIFT, SURF, BRISK) and deep learning methods. For easy reference, the different detection and classification methods are summarized in tables along with the different datasets. Furthermore, future research directions and recommendations are given in order to boost TSR’s performance.

Optimization of Triangular and Banded Matrix Operations Using 2d-Packed Layouts - Toufik Baroudi; Rachid Seghir; Vincent Loechner (ACM Transactions on Architecture and Code Optimization (TACO), 2017)
Over the past few years, multicore systems have become increasingly powerful and thereby very useful in high-performance computing. However, many applications, such as some linear algebra algorithms, still cannot take full advantage of these systems. This is mainly due to the shortage of optimization techniques dealing with irregular control structures. In particular, the well-known polyhedral model fails to optimize loop nests whose bounds and/or array references are not affine functions. This is more likely to occur when handling sparse matrices in their packed formats. In this article, we propose using 2d-packed layouts and simple affine transformations to enable optimization of triangular and banded matrix operations. The benefit of our proposal is shown through an experimental study over a set of linear algebra benchmarks.

Secure video summarization framework for personalized wireless capsule endoscopy - Rafik Hamza; Khan Muhammad; Zhihan Lv; Faiza Titouna (Pervasive and Mobile Computing, 2017)
Wireless capsule endoscopy (WCE) has several benefits over traditional endoscopy such as its portability and ease of usage, particularly for remote internet of things (IoT)-assisted healthcare services. During the WCE procedure, a significant amount of redundant video data is generated, the transmission of which to healthcare centers and gastroenterologists securely for analysis is challenging as well as wastage of several resources including energy, memory, computation, and bandwidth. In addition to this, it is inherently difficult and time consuming for gastroenterologists to analyze this huge volume of gastrointestinal video data for desired contents. To surmount these issues, we propose a secure video summarization framework for outdoor patients going through WCE procedure. In the proposed system, keyframes are extracted using a light-weighted video summarization scheme, making it more suitable for WCE. Next, a cryptosystem is presented for security of extracted keyframes based on 2D Zaslavsky chaotic map. Experimental results validate the performance of the proposed cryptosystem in terms of robustness and high-level security compared to other recent image encryption schemes during dissemination of important keyframes to healthcare centers and gastroenterologists for personalized WCE.

Modeling collaborative learning: case of clinical reasoning - Mohamed Abderraouf Ferradji; Djalal Hedjazi (Medical Technologies Journal, 2017)
Background: Collaborative learning is an important pedagogical strategy which gained a huge interest in critical domains such as the medical field. However, to ensure the quality of this learning method, it is necessary to focus intention not only on the cognitive aspect but also on the social activities that represent an essential issue during collaborative learning sessions. Our objective in this study is to highlight the collaborative aspect in the group learning method of clinical reasoning. Methods: In this work, we have focused on cognitive studies that are interested in the clinical reasoning processes, while proposing a model dedicated to the design of collaborative clinical reasoning learning environment in synchronous mode. This model is primarily interested in social activities that have a strong influence on the collaborative learning effectiveness, and they are generally treated implicitly by basing on the improvisation and spontaneity of the learners group. Results: The research idea was embodied through a collaborative learning clinical reasoning environment based on Web 2.0 technologies. We chose this technology to benefit from its ease of use and from its technical performances that can significantly contribute to the development of the cognitive and social aspects in the collaborative learning environment. Conclusion: Our first contact with medical students showed us that they are appreciating this learning method. Indeed, to evaluate objectively our choices reliability, we plan to accomplish this research with a quantitative study based on real experiences with clinicians and medical students. The suggested study will allow us to collect the necessary lessons to work in depth on the relevant questions concerning the cognitive and social activities in the collaborative clinical reasoning learning.

Implementation and Optimization of RWP Mobility Model in WSNs Under TOSSIM Simulator - Lyamine Guezouli; Kamel Barka; Souheila Bouam; Abdelmadjid Zidani (International Journal of Commu9nication Networks and Information Security (IJCNIS), 2017)
Mobility has always represented a complicated phenomenon in the network routing process. This complexity is mainly facilitated in the way that ensures reliable connections for efficient orientation of data. Many years ago, different studies were initiated basing on routing protocols dedicated to static environments in order to adapt them to the mobile environment. In the present work, we have a different vision of mobility that has many advantages due to its 'mobile' principle. Indeed, instead of searching to prevent mobility and testing for example to immobilize momentarily a mobile environment to provide routing task, we will exploit this mobility to improve routing. Based on that, we carried out a set of works to achieve this objective. For our first contribution, we found that the best way to make use of this mobility is to follow a mobility model. Many models have been proposed in the literature and employed as a data source in most studies. After a careful study, we focused on the Random Waypoint mobility model (RWP) in order to ensure routing in wireless networks. Our contribution involves a Random Waypoint model (in its basic version) that was achieved on the TOSSIM simulator, and it was considered as a platform for our second (and main) contribution, in which we suggested an approach based RWP where network nodes can collaborate and work together basing on our recommended algorithm. Such an approach offers many advantages to ensure routing in a dynamic environment. Finally, our contributions comprise innovative ideas for suggesting other solutions that will improve them.

Evaluating QoS parameters for video streaming transmission in mobile ad hoc networks - Maamar Sedrati; Hafnaoui Taleb (International Journal of Autonomic Computing, 2017)
Recently, multimedia streaming applications are deployed anywhere (homes, campuses, etc.). Delivering these applications over mobile ad hoc networks is a challenging task: first, mobile ad hoc networks are infrastructure less, with dynamic topology, and limited resources. Secondly these applications have strict quality of service (QoS) requirements given with delay, jitter, bandwidth, loss rate, etc. Several architectures have been developed. However, an important part like QoS in routing level is still omitted. In this paper, many different coding techniques for video streaming are reviewed and two routing protocols (reactive and proactive) are used to evaluate which of them can improve QoS for multimedia streaming applications. Results show that reactive protocol performs better than proactive protocol in terms of throughput and network load in high mobility, but roles are reversed in terms of loss rate and network load for large-scale networks. PNSR and Jitter are influenced by nodes numbers independently of used protocol.

Cross-layer energy efficient protocol for QoS provisioning in wireless sensor network - Amal Bourmada; Azeddine Bilami (International Journal of Systems, Control and Communications, 2017)
Ensuring (QoS) in wireless sensor networks (WSNs) is a challenging issue due to the lack of resources and energy exhausting of sensor nodes. In this paper we propose a new QoS aware routing protocol for multi-hop wireless sensor networks based on cross-layer interaction between the network, MAC and physical layers. At physical layer, a link quality estimator is studied for the purpose of evaluating link quality. At MAC layer, a differentiated services mechanism is used to distinguish between real time and non-real time packets and to allocate more channel resources for real time traffic; TDMA slots also have been modified to allocate more and earlier slots to real time packets. At network layer, a routing path selection algorithm is introduced for QoS optimisation. Simulation results show that our proposed protocol improves network's performances in terms of energy efficiency and QoS.

MONet: A framework for self-adaptive energy-aware middleware for dynamic wireless sensor network - Kamel Barka; Azeddine Bilami; Samir Gourdache (International Journal of Pervasive Computing and Communications, 2017)
The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet).

A dynamic self-organising heterogeneous routing protocol for clustered WSNs - Miloud Naidja; Azeddine Bilami (International Journal of Wireless and Mobile Computing, 2017)
Many self-adaptation routing schemes have been proposed for sensor networks. The most relevant of them consider a hierarchical topology and aim to meet energy conservation and QoS requirements in a homogeneous environment. In such networks, one specific algorithm is commonly applied by all nodes inside clusters. Contrarily, in this paper, we propose a heterogeneous routing by applying different strategies according to specific parameters at the same time inside different clusters. Moreover, each cluster can adopt different strategies at different moments under different conditions. This approach leads to a new self-adaptation protocol based on heterogeneity of the routing process in a multi-hop clustering WSN. The proposal uses a set of mechanisms that have been adopted in well-known protocols (HEEP, APTEEN, LEACH, PEGASIS, etc.) taking into account their strengths and weaknesses. Simulations under NS2 show that our proposal, based on heterogeneous routing protocol, prolongs the network lifetime with different ratios compared to HEEP, PEGASIS and others.

Multipath Routing to Improve Quality of Service for Video Streaming Over Mobile Ad Hoc Networks - Maamar Sedrati; Abderrezak Benyahia (Wireless Personal Communications, 2017)
Providing quality of service (QoS) for real-time multimedia applications such as video streaming in mobile ad hoc networks (MANETs) is an important challenge. MANETs are characterized by lack of fixed infrastructure, dynamic topology, and limited resources that make more difficult multimedia applications transport and run on this networks. To overcome this challenge, video coding techniques combined to multiple routing paths (multipath) is a promising technique for supporting transmission of multiple video streams with appropriate QoS over mobile ad hoc networks. In this paper, firstly, many issues and different techniques for video streaming over MANET have been reviewed and secondly two multi paths routing protocols (M-AODV and MDSDV) have been evaluated in order to improve QoS for real-time multimedia applications. Results show that none of these two protocols is better than the other. In certain situations (throughput and load network with high mobility) is M-AODV but in others (network load and reliability for large-scale network) is MDSDV protocol which displays good performance. It is also noted that these two protocols provide between acceptable and good quality and a small jitter regardless of nodes number in medium mobility.

PEAL: Power Efficient and Adaptive LatencyHierarchical Routing Protocol for Cluster-Based WSN - Faouzi Hidoussi; Homero Toral-Cruz; Djallel Eddine Boubiche; Rafael Martínez-Peláez; Pablo Velarde Alvarado; Romeli Barbosa; Chan Freddy (Wireless Personal Communications, 2017)
In wireless sensor networks, one of the most important constraints is the low power consumption requirement. For that reason, several hierarchical or cluster-based routing methods have been proposed to provide an efficient way to save energy during communication. However, their main challenge is to have efficient mechanisms to achieve the trade-off between increasing the network lifetime and accomplishing acceptable transmission latency. In this paper, we propose a novel protocol for cluster-based wireless sensor networks called PEAL (Power Efficient and Adaptive Latency). Our simulation results show that PEAL can extend the network lifetime about 47% compared to the classic protocol LEACH (Low-Energy Adaptive Clustering Hierarchy) and introduces an acceptable transmission latency compared to the energy conservation gain.

Genetic algorithm for attack of image encryption scheme based chaotic map - Tahar MEKHAZNIA (International Conference on Information Technology for Organizations Development (IT4OD), 2016)

A Collaborative Learning Environment of the Medical Diagnosis on the Basis of the Clinical Reasoning Theory - Mohamed-Abderraouf Ferradji (International Conference on Information and Communication Technologies for Ageing Well and e-Health, 2016)

Asymmetric End-to-End Security for Human-to-Thing Communications in the Internet of Things - SAHRAOUI Soumia (2016)

Adapting TCP protocol for wireless networks - Maamar Sedrati (International Conference on Computer Science’s Complex Systems and their Applications (ICCSA'2016), 2016)

Integrating Big data paradigm in WSNs - Sabrina Boubiche; Djallel Eddine Boubiche; Bilami Azzedine (Proceedings of the International Conference on Big Data and Advanced Wireless Technologies (BDAW '16), 2016)
WSNs consist of large number of small sensors densely deployed to monitor a phenomenon. Most of the data generated from the WSNs represent events happening at time intervals. Sometimes and according to the nature of the applications, this data stream is continuous and can reach high speeds. Therefore, adopting new techniques, platforms and tools to deal with this large amount of sensory data became necessary. Therefore, the Big Data paradigm can represent a good solution for the extraction, analysis, viewing, sharing, storage and transfer of such volume of data. This paper presents a survey on integrating Big Data tools for gathering, storing and analyzing the data generated by WSNs.

Toward Adaptive Data Aggregation Protocols in Wireless Sensor Networks - Djallel Eddine Boubiche; Sabrina Boubiche; Azeddine Bilami; Homero Toral-Cruz (Proceedings of the International Conference on Internet of things and Cloud Computing(ICC '16), 2016)
Data aggregation has emerged as a basic concept in wireless sensor networks. By combining data and eliminating redundancy, this concept showed its effectiveness in terms of reducing resources consumption. The data aggregation problem is not new and has been widely studied in wireless sensor networks. However, most of the proposed solutions are based on a static data aggregation scheme and do not consider the network constraints evolution such as energy bandwidth, overhead and transmission delay. To dynamically optimize the tradeoff between the data aggregation process and the network constraints, a new paradigm has been introduced recently named the feedback control system. The main idea is to adapt the data aggregation degree to the environment changes and the sensor network applications. The feedback control for data aggregation remains relatively a new research area and only few works have introduced this concept. Therefore this work points out this research field by surveying the different existing protocols.

Impact of routing protocols on the quality of transmission for video streaming - Sedrati Maamar; Taleb hafnaoui (Proceedings of the International Conference on Internet of things and Cloud Computing(ICC '16), 2016)
Mobile ad hoc networks are characterized by infrastructure less, dynamic topology, without any centralized administration, and limited resources witch make more difficult the stream of multimedia applications over wireless networks. Providing Quality of Service for video streaming is an important challenge. In this paper, firstly, we have reviewed many issues and different coding techniques for video streaming over MANET and secondly we propose to study two routing protocols (AODV and DSDV) to evaluate witch of them can improve QoS for real-time multimedia applications. Results show that AODV protocol performs better than DSDV in terms of throughput and network load with high mobility, but roles are reversed in terms of bit rate, loss rate and network load for large-scale networks.

ENHANCEMENT OF THE FUSION OF INCOMPATIBLE LISTS OF RESULTS - Larbi Guezouli; Imane Azzouz (International Journal of Digital Information and Wireless Communications (IJDIWC), 2016)
This work is located in the domain of distributed information retrieval (DIR). A simplified view of the DIR requires a multi-search in a set of collections, which forces the system to analyze results found in these collections, and merge results back before sending them to the user in a single list. Our work is to find a fusion method based on the relevance score of each result received from collections and the relevance of the local search engine of each collection, which is the main issue of our work.

Selection of Relevant Servers in Distributed Information Retrieval System - Sara Benhamouda; Larbi Guezouli (International Journal of Computer and Information Engineering, 2016)
Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

SEARCH OF INFORMATION BASED CONTENT IN SEMI-STRUCTURED DOCUMENTS USING INTERFERENCE WAVE - Larbi Guezouli; Hassane Essafi (International Journal of Computational Science, Information Technology and Control Engineering, 2016)
This paper proposes a semi-structured information retrieval model based on a new method for calculation of similarity. We have developed CASISS (Calculation of Similarity of Semi-Structured documents) method to quantify how two given texts are similar. This new method identifies elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of descriptors for each element, which characterize the contents of elements.It can be used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document but also the topology (position continuity) of these terms.

CAS-based information retrieval in semi-structured documents: CASISS model - Larbi Guezouli; Hassane Essafi (Journal of Innovation in Digital Ecosystems, 2016)
This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts are similar. The method can be employed in wide area of applications including content reuse detection which is a hot and challenging topic. It can be also used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document (Content Only search — CO) but also the topology (position continuity) of these terms (based on Content And Structure Search — CAS). Tracking the origin of the information in social media, copy right management, plagiarism detection, social media mining and monitoring, digital forensic are among other applications require tools such as CASISS to measure, with a high accuracy, the content overlap between two documents. CASISS identify elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of elements descriptors, which characterize the content of the elements.

A novel sensitive image encryption algorithm based on the Zaslavsky chaotic map - Rafik Hamza; Faiza Titouna (Information Security Journal: A Global Perspective, 2016)
In this article, a novel sensitive encryption scheme to secure the digital images based on the Zaslavsky chaotic map is proposed. We employ the Zaslavsky chaotic map as a pseudo-random generator to produce the key encryption of the proposed image cryptosystem. The cipher structure has been chosen based on permutation-diffusion processes, where we adopt the classic permutation substitution network, which ensures both confusion and diffusion properties for the encrypted image. Our proposed algorithm has high sensitivity in plain image and the secret key. Moreover, the results show that the characteristics of our approach have excellent performance, with high scores (NPRC = 99.61%, UACI = 33.47%, entropy (CipherImage) <img alt="" data-formula-source="{"type" : "image", "src" : "/na101/home/literatum/publisher/tandf/journals/content/uiss20/2016/uiss20.v025.i04-06/19393555.2016.1212954/20161205/images/uiss_a_1212954_ilm0001.gif"}" src="https://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/uiss20/2016/uiss20.v025.i04-06/19393555.2016.1212954/20161205/images/uiss_a_1212954_ilm0001.gif"> 8, and correlation coefficient <img alt="" data-formula-source="{"type" : "image", "src" : "/na101/home/literatum/publisher/tandf/journals/content/uiss20/2016/uiss20.v025.i04-06/19393555.2016.1212954/20161205/images/uiss_a_1212954_ilm0002.gif"}" src="https://www.tandfonline.com/na101/home/literatum/publisher/tandf/journals/content/uiss20/2016/uiss20.v025.i04-06/19393555.2016.1212954/20161205/images/uiss_a_1212954_ilm0002.gif"> 0). Experimental results have been studied and analyzed in detail with various types of security analysis. These results demonstrate that our proposed cryptosystem has highly satisfactory security performance and can withstand various attacks compared to state-of-the-art methods.

Collaborative Environment for Remote Clinical Reasoning Learning - Mohamed Abderraouf Ferradji; Abdelmadjid Zidani (International Journal of E-Health and Medical Communications (IJEHMC), 2016)
Despite the significant advances achieved these recent last years in terms of technologies widespread use in medical education, clinical reasoning learning (CRL) remains an extremely hard task in which there are still many gray areas that should be enlightened to better understand it. Furthermore, while CRL is basically a collaborative task implying the participation of many students and tutors working simultaneously on a same case, it should be considered from a social perspective. The authors followed then a collaborative-based learning approach, which consists in designing a shared workspace to support collaboration and enable social clinical knowledge acquisition. They started with a deep analysis of the CRL process in order to understand the usual way under which students learn together and then, highlight the vital collaborative learning tasks that need to be supported. The resulting designed model allowed us to shift towards Collaborative CRL (CCRL).

SDAW: secure data aggregation watermarking-based scheme in homogeneous WSNs - Djallel Eddine Boubiche; Sabrina Boubiche; Homero Toral-Cruz; Al-Sakib Khan Pathan; Azzedine Bilami; Samir Athmani (Telecommunication Systems, 2016)
Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks - Sabrina Boubiche; Djallel Eddine Boubiche; Azzedine Bilami; Homero Toral-Cruz (Sensors, 2016)
Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.