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Constructing load-balanced Degree-constrained Data Gathering Trees in Wireless Sensor Networks

机译:在无线传感器网络中构建负载平衡度受限的数据收集树

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The tree-based routing topology is widely used in various Wireless Sensor Networks (WSNs) to provide periodic data gathering. Sensors gather data and then report to the sink after data aggregation. Since sensors are usually energy limited in WSNs, it is always important to conserve node energy and extend the network lifetime that defined as the time elapsed since the network starts until the first sensor runs out of energy. Extensive research attempts to solve it as a load balancing problem aiming at balancing energy depletion among sensors. This paper studies load balancing on the tree-based data gathering networks (i.e. data gathering trees). We find that, in a Degree-constrained Data Gathering Tree (DcDGT), when the tree's height is large enough, the data traffic and load of a node are mainly determined by the distributions of its descendant nodes whose distances to it are within a certain number of hops. Based on this finding, we propose a load estimation model and further give a distributed load-balanced DcDGT construction algorithm. Simulation results demonstrate that our algorithm effectively prolongs the network lifetime and outperforms existing approaches.
机译:基于树的路由拓扑已广泛用于各种无线传感器网络(WSN)中,以提供定期的数据收集。传感器收集数据,然后在数据聚合后报告给接收器。由于传感器通常在WSN中受能量限制,因此保存节点能量并延长网络寿命(定义为自网络启动起直到第一个传感器能量用尽所经过的时间)一直很重要。广泛的研究试图将其解决为负载平衡问题,旨在平衡传感器之间的能量消耗。本文研究了基于树的数据收集网络(即数据收集树)上的负载平衡。我们发现,在度约束数据收集树(DcDGT)中,当树的高度足够大时,节点的数据流量和负载主要由与其距离在一定范围内的后代节点的分布决定。跳数。基于这一发现,我们提出了一种负载估计模型,并进一步给出了一种分布式负载均衡的DcDGT构造算法。仿真结果表明,我们的算法有效地延长了网络寿命,并且优于现有方法。

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