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A Distributed Delay-Efficient Data Aggregation Scheduling for Duty-Cycled WSNs

机译:占空比无线传感器网络的分布式时延有效数据聚合调度

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With the growing interest in wireless sensor networks (WSNs), minimizing network delay and maximizing sensor (node) lifetime are important challenges. Since the sensor battery is one of the most precious resources in a WSN, efficient utilization of the energy to prolong the network lifetime has been the focus of much of the research on WSNs. For that reason, many previous research efforts have tried to achieve tradeoffs in terms of network delay and energy cost for such data aggregation tasks. Recently, duty-cycling technique, i.e., periodically switching ON and OFF communication and sensing capabilities, has been considered to significantly reduce the active time of sensor nodes and thus extend network lifetime. However, this technique causes challenges for data aggregation. In this paper, we present a distributed approach, named distributed delay efficient data aggregation scheduling (DEDAS-D) to solve the aggregation-scheduling problem in duty-cycled WSNs. The analysis indicates that our solution is a better approach to solve this problem. We conduct extensive simulations to corroborate our analysis and show that DEDAS-D outperforms other distributed schemes and achieves an asymptotic performance compared with centralized scheme in terms of data aggregation delay.
机译:随着对无线传感器网络(WSN)的日益增长的兴趣,最小化网络延迟和最大化传感器(节点)寿命是重要的挑战。由于传感器电池是WSN中最宝贵的资源之一,因此有效利用能量来延长网络寿命一直是WSN众多研究的重点。因此,以前的许多研究工作都试图在网络延迟和能源成本方面进行折衷,以进行此类数据聚合任务。最近,已经考虑了占空比技术,即,周期性地接通和断开通信和感测能力,以显着减少传感器节点的活动时间,从而延长网络寿命。但是,这种技术给数据聚合带来了挑战。在本文中,我们提出了一种分布式方法,称为分布式延迟高效数据聚合调度(DEDAS-D),以解决占空比WSN中的聚合调度问题。分析表明,我们的解决方案是解决此问题的更好方法。我们进行了广泛的仿真,以证实我们的分析,结果表明,与集中式方案相比,DEDAS-D优于其他分布式方案,并且在数据聚合延迟方面达到了渐近性能。

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