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A Delay-Efficient Algorithm for Data Aggregation in Multihop Wireless Sensor Networks

机译:一种多跳无线传感器网络中的时延高效数据聚合算法

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Data aggregation is a key functionality in wireless sensor networks (WSNs). This paper focuses on data aggregation scheduling problem to minimize the delay (or latency). We propose an efficient distributed algorithm that produces a collision-free schedule for data aggregation in WSNs. We theoretically prove that the delay of the aggregation schedule generated by our algorithm is at most 16R+Delta -14 time slots. Here, R is the network radius and Delta is the maximum node degree in the communication graph of the original network. Our algorithm significantly improves the previously known best data aggregation algorithm with an upper bound of delay of 24D+6Delta +16 time slots, where D is the network diameter (note that D can be as large as 2R). We conduct extensive simulations to study the practical performances of our proposed data aggregation algorithm. Our simulation results corroborate our theoretical results and show that our algorithms perform better in practice. We prove that the overall lower bound of delay for data aggregation under any interference model is {rm max} {log n, R}, where n is the network size. We provide an example to show that the lower bound is (approximately) tight under the protocol interference model when r_I=r, where r_I is the interference range and r is the transmission range. We also derive the lower bound of delay under the protocol interference model when r
机译:数据聚合是无线传感器网络(WSN)中的关键功能。本文关注于数据聚合调度问题,以最大程度地减少延迟(或等待时间)。我们提出了一种高效的分布式算法,该算法可为WSN中的数据聚合生成无冲突的调度。我们从理论上证明了我们的算法生成的聚合计划的延迟最多为16R + Delta -14时隙。在此,R是网络半径,而Delta是原始网络通信图中的最大节点度。我们的算法以24D + 6Delta +16个时隙的延迟上限来显着改进以前已知的最佳数据聚合算法,其中D是网络直径(请注意,D可以大到2R)。我们进行了广泛的仿真,以研究我们提出的数据聚合算法的实际性能。我们的仿真结果证实了我们的理论结果,并表明我们的算法在实践中表现更好。我们证明,在任何干扰模型下,数据聚合的总延迟下限为{rm max} {log n,R},其中n是网络规模。我们提供一个示例来说明,当r_I = r时,在协议干扰模型下,下界是(大约)严格的,其中r_I是干扰范围,r是传输范围。当r

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