International Conference Papers

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Subject: 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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    Revisiting Directed Diffusion In The Era Of IoT-WSNs : Power Control For Adaptation to High Density
    (IEEE Xplore, 2017-08-28) Khelladi, Lyes
    Wireless Sensor Networks (WSNs) have been recognized as a crucial and enabling technology in the world of Internet of Things (IoT). However, their integration with IoT arises new design challenges, compared to conventional WSNs applications. This paper addresses the challenge of high node density and its impact on the design of IoT-WSNs routing protocols. We propose a power-aware topology control mechanism built upon the prominent routing scheme, Directed Diffusion. Moreover, we take benefit from the power-awareness feature of the topology control mechanism in order to compute an energy consumption metric, allowing the selection of energy-efficient routes. The simulation results demonstrate an improvement by the proposed protocol in terms of energy efficiency, data reporting delays and delivery success rate.
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    Collaborative KP-ABE for Cloud-Based Internet of Things Applications
    (IEEE, 2016-05-23) Touati, Lyes; Challal, Yacine
    KP-ABE mechanism emerges as one of the most suitable security protocol for asymmetric encryption. It has been widely used to implement access control solutions. However, due to its expensive overhead, it is difficult to consider this protocol in resource-limited networks, such as the IoT. As the cloud has become a key infrastructural support for IoT applications, it is interesting to exploit cloud resources to perform heavy operations. In this paper, a collaborative variant of KP-ABE named C-KP-ABE for cloud-based IoT applications is proposed. Our proposal is based on the use of computing power and storage capacities of cloud servers and trusted assistant nodes to run heavy operations. A performance analysis is conducted to show the effectiveness of the proposed solution.
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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.