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Modeling the Energy Performance of Event-Driven Wireless Sensor Network by Using Static Sink and Mobile Sink

机译:使用静态接收器和移动接收器对事件驱动的无线传感器网络的能量性能进行建模

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摘要

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.
机译:专为关键任务应用设计的无线传感器网络(WSN)的传感能力有限,尤其是能量快速消耗。对此,可以使用移动接收器来平衡WSN中的能耗,但是移动接收器的频繁位置更新可能导致数据冲突和某些特定传感器的快速能耗。本文探讨了用于事件驱动的WSN的基于最佳障碍物覆盖范围的传感器部署,其中双接收器模型旨在根据参数同时评估静态传感器,静态接收器(SS)和移动接收器(MS)的能源性能例如,传感器传输范围r和移动接收器v的速度等。此外,开发了MS移动性模型,以使SS和MS有效协作,同时通过使用累积密度函数的知识来实现​​时空能量性能效率( cdf),泊松过程和M / G / 1队列。仿真结果验证了整个网络的能源性能得到了清晰的演示,并且我们的eDSA算法比静态吸收模型更有效,将能耗降低了一半左右。此外,我们证明了我们的结果对真实感测模型具有鲁棒性,并且还通过广泛的仿真验证了我们结果的正确性。

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