Prediction- based Localization for Mobile Wireless Sensor Networks

dc.citation.epage262fr_FR
dc.citation.spage257fr_FR
dc.contributor.authorBenkhelifa, Imane
dc.contributor.authorLamini, Chakib
dc.contributor.authorAzouz, Hichem
dc.contributor.authorMoussaoui, Samira
dc.date.accessioned2014-10-08T10:49:30Z
dc.date.available2014-10-08T10:49:30Z
dc.date.issued2014-09
dc.description.abstractIn 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.fr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/687
dc.publisherIEEEfr_FR
dc.relation.ispartofThe 17th International Conference on Network-Based Information Systems (NBiS)fr_FR
dc.relation.placeSalerno, Italyfr_FR
dc.rights.holderIEEEfr_FR
dc.structureCalcul Pervasif et Mobilefr_FR
dc.structureRéseaux de Capteurs et Applicationsfr_FR
dc.subjectLocalizationfr_FR
dc.subjectPredictionfr_FR
dc.subjectMobile Anchorfr_FR
dc.subjectMobile Wireless Sensor Networksfr_FR
dc.titlePrediction- based Localization for Mobile Wireless Sensor Networksfr_FR
dc.typeConference paper
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