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Dynamic data aggregation for energy optimization in multi-hop Wireless Sensor Networks

机译:动态数据聚合,用于多跳无线传感器网络中的能源优化

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This paper proposes a model where the energy usage of sensor nodes in a multi-hop Wireless Sensor Network (WSN) is optimized by using data aggregation, a technique which discards “unnecessary” packets so as to save bandwidth. It does so in two steps; first of which uses an Exponential Weighted Moving Average (EWMA) data aggregation technique to compare the current data value with all the previous values before deciding whether to forward or drop the packet. The second step optimizes the network even further by considering readings from neighboring sensors into the equation. Some flexibility has been designed in the algorithm allowing the precision level to be adjusted based on the users requirements. Simulated results show how the scheme reduces the number of packets transmitted and the normalized energy consumed by the nodes.
机译:本文提出了一个模型,其中通过使用数据聚合来优化多跳无线传感器网络(WSN)中传感器节点的能量使用,该技术会丢弃“不必要”的数据包以节省带宽。它分两步完成;首先,它使用指数加权移动平均(EWMA)数据聚合技术将当前数据值与所有先前的值进行比较,然后再决定是转发还是丢弃数据包。第二步甚至通过考虑将相邻传感器的读数纳入方程式来进一步优化网络。算法中已设计了一些灵活性,可以根据用户要求调整精度级别。仿真结果表明该方案如何减少传输的数据包数量以及节点消耗的标准化能量。

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