International Conference Papers
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Item DPFTT: Distributed Particle Filter for Target Tracking in the Internet of Things(IEEE, 2023-11-07) Boulkaboul, Sahar; Djenouri, Djamel; Bagaa, MiloudA 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.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, MohandThis 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.Item UDEPLOY: User-Driven Learning for Occupancy Sensors DEPLOYment In Smart Buildings(IEEE, 2018-03) Laidi, Roufaida; Djenouri, DjamelA solution for motion sensors deployment in smart buildings is proposed. It differentiates the monitored zones according to their occupancy, where highly-occupied zones have higher coverage requirements over low-occupied zones, and thus are assigned higher granularity in the targeted coverage (weights). The proposed solution is the first that defines a user-driven approach, which uses sampling of occupants’ behavior to determine the zones and the coverage weights. The samples are acquired during a short learning phase and then used to derive a graph model. The latter is plugged into a greedy, yet effective, algorithm that seeks optimal placement for maximizing detection accuracy while reducing the cost (number of sensors). Practical aspects such as the scalability and the applicability of the solution are considered. A simulation study that compares the proposed solution with two state-of-the-art solutions shows the superiority of the proposed approach in the accuracy of detection (increased coverage), and scalability (reduced runtime).Item ADABCAST: ADAptive BroadCAST Approach for Solar Energy Harvesting Wireless Sensor Networks(IEEE, 2017-04) Khiati, Mustapha; Djenouri, DjamelThe problem of message broadcasting from the base station (BS) to sensor nodes (SNs) in solar energy harvesting wireless sensor networks (EHWSN) is considered in this paper. The aim is to ensure fast and reliable broadcasting without interfering with upstream communications (from SNs to BS), whilst taking into account energy harvesting constraints. An adaptive approach is proposed where the BS first selects the broadcast time slots, given a wake-up schedule for the SNs (the time slots where the SN are active and in receiving mode). Hence, the SNs adapt their schedules. This is then iterated seeking optimal selection of the broadcast time slots, so as to minimize broadcast overhead (transmitted messages) and latency. Our approach enables fast broadcast and eliminates the need for adding protocol overhead (redundancy), compared to the existing solutions. Hidden Markov Model (HMM) and Baum-Welch learning algorithm are used for this purpose. Numerical results confirm that our scheme performs the broadcast operation in less time, and by reducing the broadcast overhead, as compared to state-of-the-art approaches.Item An oscillation-based algorithm for reliable vehicle detection with magnetic sensors(IEEE, 2016-04) Djenouri, Djamel; Doudou, Messaoud; Kafi, Mohamed AmineVehicle monitoring using a wireless sensor network is considered in this paper, where a new algorithm is proposed for vehicle detection with magnetic sensors. The proposed algorithm is based on processing the magnetic signal and thoroughly analyzing the number/direction of its oscillations. The main feature of the proposed algorithm over the state-of-the-art ones is its capability to detect vehicles with different shapes of signatures, while most state-of-the-art algorithms assume regular shapes of signatures. This makes the algorithm effective with all types of magnetic sensors. The proposed algorithm has been implemented on MICAz sensor motes and tested in real world scenarios. Results show reliability beyond 93% in all samples, and more than 95% in most of them.Item Congestion Detection Strategies in Wireless Sensor Networks: A Comparative Study with Testbed Experiments(Elsevier, 2014-09) Kafi, Mohamed Amine; Djenouri, Djamel; Ouadjaout, Abdelraouf; Badache, NadjibEvent based applications of Wireless Sensor Networks (WSNs) are prone to traffic congestion, where unpredicted event detection yields simultaneous generation of traffic at spatially co-related nodes, and its propagation towards the sink. This results in loss of information and waste energy. Early congestion detection is thus of high importance in such WSN applications to avoid the propagation of such a problem and to reduce its consequences. Different detection metrics are used in the congestion control literature. However, a comparative study that investigates the different metrics in real sensor motes environment is missing. This paper focuses on this issue and compares some detection metrics in a testbed network with MICAz motes. Results show the effectiveness of each method in different scenarios and concludes that the combination of buffer length and channel load constitute the better candidate for early and fictive detection.Item Interference-aware Congestion Control Protocol for Wireless Sensor Networks(Elsevier, 2014-09) Kafi, Mohamed Amine; Djenouri, Djamel; Ben Othman, Jalel; Ouadjaout, Abdelraouf; Bagaa, Miloud; Lasla, Noureddine; Badache, NadjibThis paper deals with congestion and interference control in wireless sensor networks (WSN), which is essential for improving the throughput and saving the scarce energy in networks where nodes have different capacities and traffic patterns. A scheme called IACC (Interference-Aware Congestion Control) is proposed. It allows maximizing link capacity utilization for each node by controlling congestion and interference. This is achieved through fair maximum rate control of interfering nodes in inter and intra paths of hot spots. The proposed protocol has been evaluated by simulation, where the results rival the effectiveness of our scheme in terms of energy saving and throughput. In particular, the results demonstrate the protocol scalability and considerable reduction of packet loss that allow to achieve as high packet delivery ratio as 80% for large networks.Item BA: Game Theoretical Approach for Energy-Delay Balancing in Distributed Duty-Cycled MAC Protocols of Wireless Networks(ACM, 2014-07-14) Doudou, Messaoud; M. Barcelo-Ordinas, Jose; Djenouri, Djamel; Garcia-Vidal, Jorge; Badache, NadjibOptimizing energy consumption and end-to-end (e2e) packet delay in energy constrained distributed wireless networks is a conflicting multi-objective optimization problem. This paper investigates this trade-off from a game-theoretic perspective, where the two optimization objectives are considered as virtual game players that attempt to optimize their utility values. The cost model of each player is mapped through a generalized optimization framework onto protocol specific MAC parameters. A cooperative game is then defined, in which the Nash Bargaining solution assures the balance between energy consumption and e2e packet delay. For illustration, this formulation is applied to three state-of-the-art wireless sensor network MAC protocols; X-MAC, DMAC, and LMAC as representatives of preamble sampling, slotted contention-based, and frame-based MAC categories, respectively. The paper shows the effectiveness of such framework in optimizing protocol parameters for achieving a fair energy-delay performance trade-off, under the application requirements in terms of initial energy budget and maximum e2e packet delay. The proposed framework is scalable with the increase in the number of nodes, as the players represent the optimization metrics instead of nodes.Item Parallel BSO Algorithm for Association Rules Mining Using Master/Worker Paradigm(2015-09-06) Djenouri, Youcef; Bendjoudi, Ahcène; Djenouri, Djamel; Habbas, ZinebThe extraction of association rules from large transactional databases is considered in the paper using cluster architecture parallel computing. Motivated by both the successful sequential BSO-ARM algorithm, and the strong matching between this algorithm and the structure of the cluster architectures, we present in this paper a new parallel ARM algorithm that we call MW-BSO-ARM for Master/Workers version of BSO-ARM. The goal is to deal with large databases by minimizing the communication and synchronization costs, which represent the main challenges that faces any cluster architecture. The experimental results are very promising and show clear improvement that reaches 300% for large instances. For examples, in big transactional database such as WebDocs, the proposed approach generates 107 satisfied rules in only 22 minutes, while a previous GPU-based approach cannot generate more than 103 satisfied rules into 10 hours. The results also reveal that MWBSO-ARM outperforms the PGARM cluster-based approach in terms of computation time.Item On the Effect of Sensing-Holes in PIR-based Occupancy Detection Systems(2016-02-20) Ouadjaout, Abdelraouf; Lasla, Noureddine; Djenouri, Djamel; Zizoua, CherifSensing-holes in PIR-based motion detection systems are considered, and their impact on occupancy monitoring applications is investigated. To our knowledge, none of prior works on PIR-based systems consider the presence of these holes, which represents the major cause for low precision of such systems in environments featured with very low mobility of occupants, such as working offices. We consider optimal placement of PIRs that ensures maximum coverage in presence of holes. The problem is formulated as a mixed integer linear programming optimization problem (MILP). Based on this formulation, an experimental study on a typical working office has been carried out. The empirical results quantify the effects of the holes on the detection accuracy and demonstrate the enhancement provided by the optimal deployment of the solution.