title: Modeling the energy performance of event-driven wireless sensor network by using static sink and mobile sink.
abstract: Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations.
authors.affiliation: Global COE Program International Research and Education Center for Ambient SoC, Waseda University, Tokyo, 169-8555, Japan. chenjiehui0574@fuji.waseda.jp
authors.forename: Jiehui
authors.initials: J
authors.lastname: Chen
authors.forename: Mariam B
authors.initials: MB
authors.lastname: Salim
authors.forename: Mitsuji
authors.initials: M
authors.lastname: Matsumoto
mesh_terms: D003195:Computer Communication Networks / Q000295:instrumentation* / Q000458:organization & administration; D003198:Computer Simulation; D004526:Efficiency; D004560:Electricity; D008954:Models, Biological; D008962:Models, Theoretical; D009038:Motion; D058998:Remote Sensing Technology / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D013686:Telemetry / Q000295:instrumentation / Q000379:methods; D059015:Wireless Technology / Q000295:instrumentation*