International Conference Papers

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Author: search.filters.author.Djenouri, DjamelSubject: search.filters.subject.Internet of Things

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    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.
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    On the Relevance of Using Interference and Service Differentiation Routing in the Internet-of-Things
    (Springer, 2013-08) Bagula, Antoine; Djenouri, Djamel; Karbab, Elmouatezbillah
    Next generation sensor networks are predicted to be deployed in the Internet-of-the-Things (IoT) with a high level of heterogeneity. They will be using sensor motes which are equipped with different sensing and communication devices and tasked to deliver different services leading to different energy consumption patterns. The application of traditional wireless sensor routing algorithms designed for sensor motes expanding the same energy to such heterogeneous networks may lead to energy unbalance and subsequent short-lived sensor networks resulting from routing the sensor readings over the most overworked sensor nodes while leaving the least used nodes idle. Building upon node interference awareness and sensor devices service identification, we assess the relevance of using a routing protocol that combines these two key features to achieve efficient traffic engineering in IoT settings and its relative efficiency compared to traditional sensor routing. Performance evaluation with simulation reveals clear improvement of the proposed protocol vs. state of the art solutions in terms of load balancing, notably for critical nodes that cover more services. Results show that the proposed protocol considerably reduce the number of packets routed by critical nodes, where the difference with the compared protocol becomes more and more important as the number of nodes increases. Results also reveal clear reduction in the average energy consumption.