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Delay and Energy Efficiency Tradeoffs for Data Collections and Aggregation in Large Scale Wireless Sensor Networks

机译:大规模无线传感器网络中数据收集和聚集的延迟和能效权衡

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In this paper, we study efficient data collection and aggregation problem in wireless sensor networks. We first propose efficient distributed algorithms for data collection problem with approximately the minimum delay, or the minimum number of messages to be sent by all wireless nodes, or the minimum total energy consumption by all wireless nodes respectively. For example, given an algorithm A for data collection, let e_T, e_M, and e_E be the approximation ratio of A in terms of time complexity, message complexity, and energy complexity respectively. We then show that, for data collection, there are networks of n nodes and maximum degree △, such that e_Me_E = Ω(△) for any algorithm. In addition, we analytically proved that all our proposed methods are either optimum or within constants factor of the optimum. We further present the message, energy, time complexity and studied the complexity tradeoffs for data aggregation problem.
机译:在本文中,我们在无线传感器网络中研究了高效的数据收集和聚合问题。我们首先提出了有效的分布式算法,用于数据收集问题,包括所有无线节点的最小延迟,或者分别由所有无线节点发送的最小消息数,或分别由所有无线节点的最小总能量消耗。例如,给定用于数据收集的算法a,让e_t,e_m和e_e分别是时间复杂度,消息复杂性和能量复杂性的近似比。然后,我们表明,对于数据收集,存在N个节点和最大程度的网络,使得任何算法的E_ME_E =Ω(△)。此外,我们分析证明,我们所有所提出的方法都是最佳的或在最佳常数因子内。我们进一步提出了消息,能源,时间复杂性,并研究了数据聚合问题的复杂性权衡。

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