International Conference Papers

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Author: search.filters.author.Boulkaboul, Sahar

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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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    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.
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    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.