Browsing by Author "Boulkaboul, Sahar"

Now showing 1 - 7 of 7
  • Thumbnail Image
    Item
    Car Park Management with Networked Wireless Sensors and Active RFID
    (CERIST, 2015-03-30) Djenouri, Djamel; Karbab, Elmouatezbillah; Boulkaboul, Sahar; Bagula, Antoine
    This paper considers automatic car park management, which becomes an inevitable option to rationalize traffic management in modern cities. Integration of networked sensor/ actuator and radio frequency identification (RFID) technologies is explored to enable sophisticated services via the Internet in the emerging internet of things (IoT) context. Based on this integration, we propose a scalable and low-cost car parking framework (CPF). A preliminary prototype implementation and experimentation of some modules of the proposed CFP has been performed. The clustering of sensors (sensing boards) into a single mote using the standard I2C protocol has been explored in the prototype, and experimental results demonstrate considerable reduction in cost and energy consumption.
  • Thumbnail Image
    Item
    DFIOT: Data Fusion for Internet of Things
    (Springer Science, 2020) Boulkaboul, Sahar; Djenouri, Djamel
    In Internet of Things (IoT) ubiquitous environments, a high volume of heterogeneous data is produced from different devices in a quick span of time. In all IoT applications, the quality of information plays an important role in decision making. Data fusion is one of the current research trends in this arena that is considered in this paper. We particularly consider typical IoT scenarios where the sources measurements highly conflict, which makes intuitive fusions prone to wrong and misleading results. This paper proposes a taxonomy of decision fusion methods that rely on the theory of belief. It proposes a data fusion method for the Internet of Things (DFIOT) based on Dempster–Shafer (D–S) theory and an adaptive weighted fusion algorithm. It considers the reliability of each device in the network and the conflicts between devices when fusing data. This is while considering the information lifetime, the distance separating sensors and entities, and reducing computation. The proposed method uses a combination of rules based on the Basic Probability Assignment (BPA) to represent uncertain information or to quantify the similarity between two bodies of evidence. To investigate the effectiveness of the proposed method in comparison with D–S, Murphy, Deng and Yuan, a comprehensive analysis is provided using both benchmark data simulation and real dataset from a smart building testbed. Results show that DFIOT outperforms all the above mentioned methods in terms of reliability, accuracy and conflict management. The accuracy of the system reached up to 99.18% on benchmark artificial datasets and 98.87% on real datasets with a conflict of 0.58%. We also examine the impact of this improvement from the application perspective (energy saving), and the results show a gain of up to 90% when using DFIOT.
  • Thumbnail Image
    Item
    DPFTT: Distributed Particle Filter for Target Tracking in the Internet of Things
    (IEEE, 2023-11-07) Boulkaboul, Sahar; Djenouri, Djamel; Bagaa, Miloud
    A novel distributed particle filter algorithm for target tracking is proposed in this paper. It uses new metrics and addresses the measurement uncertainty problem by adapting the particle filter to environmental changes and estimating the kinematic (motion-related) parameters of the target. The aim is to calculate the distance between the Gaussian-distributed probability densities of kinematic data and to generate the optimal distribution that maximizes the precision. The proposed data fusion method can be used in several smart environments and Internet of Things (IoT) applications that call for target tracking, such as smart building applications, security surveillance, smart healthcare, and intelligent transportation, to mention a few. The diverse estimation techniques were compared with the state-of-the-art solutions by measuring the estimation root mean square error in different settings under different conditions, including high-noise environments. The simulation results show that the proposed algorithm is scalable and outperforms the standard particle filter, the improved particle filter based on KLD, and the consensus-based particle filter algorithm.
  • Thumbnail Image
    Item
    FDAP: Fast Data Aggregation Protocol in Wireless Sensor Networks
    (IEEE/Springer, 2012-08) Boulkaboul, Sahar; Djenouri, Djamel; Badache, Nadjib
    This paper focuses on data aggregation latency in wireless sensors networks. A distributed algorithm to generate a collision-free schedule for data aggregation in wireless sensor networks is proposed. The proposed algorithm is based on maximal independent sets. It modifies DAS scheme and proposes criteria for node selection amongst available competitors. The selection objective function captures the node degree (number of neighbors) and the level (number of hops) contrary to DAS that simply uses node ID. The proposed solution augments parallel transmissions, which reduces the latency. The time latency of the aggregation schedule generated by the proposed algorithm is also minimized. The latency upper-bound of the schedule is 17R+6Δ+8 time-slots, where R is the network radius and Δ is the maximum node degree. This clearly outperforms the state-of-the-art distributed data aggregation algorithms, whose latency upper-bound is not less than 48R+6Δ+16 time-slots. The proposed protocol is analyzed through a comparative simulation study, where the obtained results confirm the improvement over the existing solutions.
  • Thumbnail Image
    Item
    IoT-DMCP: An IoT data management and control platform for smart cities
    (SCITEPRESS – Science and Technology Publications, 2019) Boulkaboul, Sahar; Djenouri, Djamel; Bouhafs, Sadmi; Belaid, Mohand
    This paper presents a design and implementation of a data management platform to monitor and control smart objects in the Internet of Things (IoT). This is through IPv4/IPv6, and by combining IoT specific features and protocols such as CoAP, HTTP and WebSocket. The platform allows anomaly detection in IoT devices and real-time error reporting mechanisms. Moreover, the platform is designed as a standalone application, which targets at extending cloud connectivity to the edge of the network with fog computing. It extensively uses the features and entities provided by the Capillary Networks with a micro-services based architecture linked via a large set of REST APIs, which allows developing applications independently of the heterogeneous devices. The platform addresses the challenges in terms of connectivity, reliability, security and mobility of the Internet of Things through IPv6. The implementation of the platform is evaluated in a smart home scenario and tested via numeric results. The results show low latency, at the order of few ten of milliseconds, for building control over the implemented mobile application, which confirm realtime feature of the proposed solution.
  • Thumbnail Image
    Item
    Minimisation du délai d'agrégation de données dans les réseaux de capteurs
    (Université Abderrahmane Mira de Béjaia, 2009) Boulkaboul, Sahar; Badache, Nadjib; Djenouri, Djamel
    La méthode d’agrégation de données a été proposée comme un nouveau paradigme utile pour le routage dans les réseaux de capteurs. L’idée de base de cette méthode consiste à combiner les données provenant de différents noeuds sources en éliminant les redondances existantes, et en minimisant aussi le nombre de transmissions possibles pour économiser la quantité d’énergie consommée. Plusieurs protocoles d’agrégation qui minimisent la consommation de l’énergie souffrent de l’augmentation du délai de livraison de données à cause du délai d’attente qu’un agrégateur peut attendre de ses fils pour collecter les données et les envoyer jusqu’au puits. Les collisions de communications sont la raison primaire pour la longue latence dans l’agrégation de données. Après ce constat, un état de l’art des travaux de minimisation du délai dans le paradigme de l’agrégation de données est élaboré. Cet état de l’art présente l’ensemble des solutions proposées dans ce domaine ainsi que des discussions décrivant les avantages et les limitations des différentes solutions. Basées sur les discussions et critiques effectuées, nous avons proposé une amélioration d’un protocole qui minimise le délai de bout-en-bout de l’agrégation de données en vue de le rendre plus efficace en terme de latence. Pour cela, une description de ce protocole est d’abord donnée décrivant ses caractéristiques et son principe de fonctionnement. Par la suite, des améliorations à ce protocole ont été proposées, elles consistent essentiellement en L’amélioration d’une approche distribuée afin de prendre en compte la topologie du réseau et le nombre de voisins lors de la construction de l’arbre d’agrégation, et l’augmentation des transmissions parallèles durant l’agrégation de données en évitant les collisions. Nous avons comparé notre solution avec un autre protocole que nous avons implémenté en utilisant l'environnement Python. Les résultats de simulation démontrent que le protocole proposé permet de réduire significativement dans le temps d’agrégation.
  • Thumbnail Image
    Item
    Networked Wireless Sensors, Active RFID, and Handheld Devices for Modern Car Park Management: WSN, RFID, and Mob Devs for Car Park Management
    (IGI Global, 2015-07-01) Djenouri, Djamel; Karbab, Elmouatezbillah; Boulkaboul, Sahar; Bagula, Antoine
    Networked wireless sensors, actuators, RFID, and mobile computing technologies are explored in this paper on the quest for modern car park management systems with sophisticated services over the emerging internet of things (IoT), where things such as ubiquitous handheld computers, smart ubiquitous sensors, RFID readers and tags are expected to be interconnected to virtually form networks that enable a variety of services. After an overview of the literature, the authors propose a scalable and lowcost car parking framework (CPF) based on the integration of aforementioned technologies. A preliminary prototype implementation has been performed, as well as experimentation of some modules of the proposed CPF. The results demonstrate proof of concept, and particularly reveal that the proposed approach for WSN deployment considerably reduces the cost and energy consumption compared to existing solutions.