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Item Modified Elastic Routing to support Sink Mobility Characteristics in Wireless Sensor Networks(Springer's Lecture Notes in Computer Science, 2016-09) Benkhelifa, Imane; Belmouloud, Nassim; Tabia, Yasmine; Moussaoui, SamiraThis paper presents improvements for the geographic routing protocol Elastic so to support the different sink mobility characteristics. We have proposed a strategy to support multiple mobile sinks; tested Elastic under high speeds of the mobile sink; proposed two strategies in case of the sink temporary absence and finally proposed to predict the sink location by the source node and then by all the nodes. Simulation results show that our propositions improve much the delivery ratio and reduce the delivery delay.Item Performance Analysis of Sinks Mobility in Geographic Routing for Wireless Sensor Networks(CERIST, 2015-04-12) Benkhelifa, Imane; Belmouloud, Nassim; Tabia, Yasmina; Moussaoui, SamiraThis paper presents a performance analysis of sinks mobility in geographic routing based on performance evaluation of two geographic routing protocols namely GPSR with static sinks and Elastic with mobile sinks. Among the scenarios, we observe also the impact of using multi-mobile-sinks, in addition to the effect of mobility model through changing the sink’s trajectory and speed. We analyze the performance results by calculating the delivery ratio of the transmitted packets, as well as the average delay of transmission and the number of hops necessary to transmit successfully a packet from the source to the sink. We show that mobile sinks can play a major role in prolonging the network lifetime and the efficiency of a geographic routing protocol.Item Mobile sink and power management for efficient data dissemination in wireless sensor networks(Springer US, 2014-11) Guerroumi, Mohamed; Badache, Nadjib; Moussaoui, SamiraData dissemination in wireless sensor networks is the main goal and the final waited objective of the sensor network deployment. In such environment which consists of a large number of low cost devices, sensor nodes generate sensed data of stimulus and forward them to sinks via wireless multi-hops communication. In typical wireless sensor network, the sensor nodes are equipped with irreplaceable batteries and characterized by limited computing capability. Therefore, minimizing the energy consumption of the sensor nodes and thus maximizing the lifetime of sensor networks is one of the most important research issues. In this paper, we present new data dissemination protocol based energy-efficient called energy-based data dissemination protocol. In this protocol, we propose new energy management scheme using a dynamic power threshold and we introduce also new sink mobility scheme to balance the network load between sensor nodes and thus improve the performances. Firstly, in the initialization phase, the sensor nodes organized under clusters and cluster head should be selected for each cluster. Secondly, in the data dissemination phase, the cluster head collects and transmits the sensed data based on the data dissemination process. In this phase, sensor sink may move toward any cluster based on its sensed data frequency to minimize energy consumption of sensor nodes near the fixed sinks due to relaying of large amount of data. The simulation result shows that the proposal protocol permits to reduce the energy consumption and prolong the network life.Item Prediction- based Localization for Mobile Wireless Sensor Networks(IEEE, 2014-09) Benkhelifa, Imane; Lamini, Chakib; Azouz, Hichem; Moussaoui, SamiraIn this paper, we propose two extensions of SDPL (Speed and Direction Prediction-based Localization) method. The first is called MA-SDPL (Multiple Anchors SDPL) which uses multiple mobile anchors instead of only one. Each anchor has its own trajectory and its own departure point. The goal is to ensure a total coverage of the sensor field and to multiply the chance of receiving anchor beacons. Anchor Beacons help localizing mobile sensors. As a consequence, the location estimation will be enhanced. The second method deals with one mobile anchor but with the ability of multi-hoping, that is, when a sensor estimates that it is well enough localized, it sends beacons to its hneighborhood about its current location, hence, it plays the role of an additional anchor. This solution reduces the cost comparing to when using multiple anchors and allows rapid location propagation. Simulation results show that the two extensions improve better the ratio of localized sensors and reduce the location error compared to the basic SDPL. We have also tested them in a noisy environment to be closer to a real deployment.Item Prediction-based Localization for Mobile Wireless Sensor Networks(CERIST, 2014-06-05) Benkhelifa, Imane; Lamini, Chakib; Azouz, Hichem; Moussaoui, SamiraIn this paper, we propose two extensions of SDPL (Speed and Direction Prediction-based Localization) method. The first is called MA-SDPL (Multiple Anchors SDPL) which uses multiple mobile anchors instead of only one. Each anchor has its own trajectory and its own departure point. The goal is to ensure a total coverage of the sensor field and to multiply the chance of receiving anchor beacons. Anchor Beacons help localizing mobile sensors. As a consequence, the location estimation will be enhanced. The second method deals with one mobile anchor but with the ability of multi-hoping, that is, when a sensor estimates that it is well enough localized, it sends beacons to its h-neighborhood about its current location, hence, it plays the role of an additional anchor. This solution reduces the cost comparing to when using multiple anchors and allows rapid location propagation. Simulation results show that the two extensions improve better the ratio of localized sensors and reduce the location error compared to the basic SDPL. We have also tested them in a noisy environment to be closer to a real deployment.Item Disaster Management Projects using Wireless Sensor Networks(Barolli et al., 2014-05-13) Benkhelifa, Imane; Nouali-Taboudjemat, Nadia; Moussaoui, SamiraThere are numerous projects dealing with disaster management and emergency response that use wireless sensor networks technologies. Indeed, WSNs offer a good alternative compared to traditional ad hoc networks. Air pollution monitoring, forest fire detection, landslide detection, natural disaster prevention, industrial sense and control applications, dangerous gas leakage, water level monitoring, vibration detection to prevent an earthquake, radiation monitoring are examples of the WSN applications related to disaster management. This paper presents an overview of the recent projects using WSN to collect data in disaster areas.Item Speed and Direction Prediction-based Localization for Mobile Wireless Sensor Networks(CERIST, 2012) Benkhelifa, Imane; Moussaoui, SamiraPlusieurs techniques de localisation ont été proposées pour les réseaux de capteurs sans fils. Cependant, peu considèrent la mobilité des capteurs. Dans cet article, nous proposons une technique de localisation efficace et pratique spécialement conçue pour les réseaux de capteurs mobiles, nommée Speed and Direction Prediction-based Localization. Cette méthode utilise une seule ancre mobile traversant la zone de déploiement avec une trajectoire prédéfinie tout en diffusant sa position à ses capteurs voisins. Nous nous intéressons principalement à l’amélioration de la précision et l’efficacité du positionnement avec une meilleure utilisation des informations collectées par un capteur. En utilisant les informations de positionnement précédentes, le nœud prédit sa vitesse et sa direction de déplacement afin de rapprocher sa position estimée vers sa position réelle. L’évaluation de notre solution montre que cette technique de prédiction bénéficie à la fois, de la prédiction et la trajectoire de l’ancre mobile, d’une manière plus efficace que des solutions précédentes. Les résultats de simulation montrent que notre algorithme dépasse la méthode de Monté Carlo conventionnel et sa variante MCB en diminuant l’erreur de positionnement par plus de 56%. Abstract : Many low-cost localization techniques have been proposed for wireless sensor networks. However, few consider the mobility of networked sensors. In this paper, we propose an effective and practical localization technique especially designed for mobile sensor networks called Speed and direction Prediction-based Localization. It uses a single mobile anchor travelling with a predefined trajectory while periodically broadcasts its current location coordinates to the nearby sensors. We concentrate on improving the localization accuracy and efficiency by making better use of the information a sensor node gathers. Using previous location information, the node predicts its speed and direction to move the estimated position closer to its real position. The evaluation of our solution shows that our technique takes benefit from both, prediction and anchor trajectory, in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors by up to 56%.Item Speed and Direction Prediction-based Localization for Mobile Wireless Sensor Networks(CARI, 2012-10) Benkhelifa, Imane; Moussaoui, SamiraIn this paper, we propose an efficient and practical localization technique especially designed for mobile sensor networks. It uses a single mobile anchor travelling with a predefined trajectory while periodically broadcasts its current location coordinates to the nearby sensors. Using previous location information, the node predicts its speed and direction. The evaluation of our solution shows that our technique takes benefit from both, prediction and anchor trajectory, in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes and its variant MCB.Item APPL: Anchor Path Planning based Localization for Wireless Sensor Networks(Mosharaka for Researches and Studies, 2011-07) Benkhelifa, Imane; Moussaoui, SamiraIn this paper, we study the static path planning problem with wireless sensor network localization as the primary objective. We consider a model in which sensors are assumed to be uniformly deployed to a predefined deployment area.We then deploy a mobile anchor to enable the localization of the sensor nodes. The anchor follows a predetermined static path while periodically broadcasting its current location coordinates to the nearby sensors.The static path planning problem looks for good paths that result in better localization accuracy and coverage of the sensor network while keeping the path length bounded. We propose three new path types, SQUARES, ARCHIMEDEAN SPIRAL and WAVES that are specifically designed to reduce the collinearity of anchor messages during localization. We compare our solution with existing ones (SCAN and HILBERT trajectories) using a very simple localization algorithm. The evaluation shows that our solutions cope with collinearity and path length in a more effective manner than previous solutions. Our solutions provide significantly better localization accuracy and coverage.Item Speed and Direction Prediction-based Localization for Mobile Wireless Sensor Networks(IEEE CONFERENCE PUBLICATIONS, 2012) Benkhelifa, Imane; Moussaoui, SamiraMany low-cost localization techniques have been proposed for wireless sensor networks. However, few consider the mobility of networked sensors. In this paper, we propose an effective and practical localization technique especially designed for mobile sensor networks called Speed and direction Prediction-based Localization. It uses a single mobile anchor travelling with a predefined trajectory while periodically broadcasts its current location coordinates to the nearby sensors. We concentrate on improving the localization accuracy and efficiency by making better use of the information a sensor node gathers. Using previous location information, the node predicts its speed and direction to move the estimated position closer to its real position. The evaluation of our solution shows that our technique copes with prediction and anchor trajectory in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors by up to 56%.