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Quick, Decentralized, Energy-Efficient One-Shot Max Function Computation Using Timer-Based Selection

机译:使用基于计时器的选择进行快速,分散,节能的一键最大函数计算

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摘要

In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.
机译:在几个无线传感器网络中,确定传感器读数的最大值并确定引起该问题的传感器是很重要的。我们提出了一种新颖的,分散的,可扩展的,高能效的,基于计时器的单次最大函数计算(TMC)算法。在其中,传感器节点不会以中央预定义的顺序传输其读数。取而代之的是,将节点分组为群集,并且计算在两个竞争阶段进行。首先,每个群集中的节点使用计时器方案相互竞争,以将其读数传输到其群集头。此后,群集头使用计时器方案将群集中的最高传感器读数发送到融合节点。一个新的挑战是使用计时器方案会导致冲突,这会使算法失败。我们对算法进行了优化,以最大程度地减少确定最大值所需的平均时间,该时间受无法找到最大值的概率的约束。与文献中提出的方法相比,TMC显着降低了平均功能计算时间,平均传输次数和平均能耗。

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