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Distributed Low-Latency Data Aggregation for Duty-Cycle Wireless Sensor Networks

机译:占空比无线传感器网络的分布式低延迟数据聚合

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Data aggregation is an essential operation for the sink to obtain summary information in a wireless sensor network (WSN). The problem of minimum latency aggregation schedule (MLAS) which seeks a fastest and conflict-free aggregation schedule has been well studied when nodes are always awake. However, in duty-cycle WSNs, nodes can only receive data in the active state. In such networks, it is of great importance to exploit the limited active time slots to reduce aggregation latency. Unfortunately, few studies have addressed this issue, and most previous aggregation methods rely on fixed structures which greatly limit the exploitation of the active time slots from neighbors. In this paper, we investigate the MLAS problem in duty-cycle WSNs without considering structures. Two distributed aggregation algorithms are proposed, in which the aggregation tree and a conflict-free schedule are generated simultaneously to make use of the active time slots from all neighbors. Compared with the previous centralized and distributed methods, the aggregation latency and the utilization ratio of available time slots are greatly improved. This paper also proposes several adaptive strategies for handling network topology changes without increasing the aggregation latency. The theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency and communication cost.
机译:数据聚合是接收器在无线传感器网络(WSN)中获取摘要信息的基本操作。当节点始终处于唤醒状态时,寻求最快和无冲突的聚合计划的最小延迟聚合计划(MLAS)问题已得到充分研究。但是,在占空比WSN中,节点只能在活动状态下接收数据。在这样的网络中,利用有限的活动时隙来减少聚合等待时间非常重要。不幸的是,很少有研究解决这个问题,并且大多数先前的聚合方法依赖于固定结构,这极大地限制了邻居对活动时隙的利用。在本文中,我们在不考虑结构的情况下研究了占空比WSN中的MLAS问题。提出了两种分布式聚合算法,其中聚合树和无冲突调度同时生成,以利用所有邻居的活动时隙。与以前的集中式和分布式方法相比,极大地提高了聚合时延和可用时隙的利用率。本文还提出了几种在不增加聚合延迟的情况下处理网络拓扑变化的自适应策略。理论分析和仿真结果验证了所提算法在时延和通信成本方面具有较高的性能。

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