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Quick, decentralized, 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,一次性的最大函数计算

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In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. This has been referred to as the max function computation problem in the literature. We propose a novel, decentralized, timer-based max function computation (TMC) algorithm. In it, the sensors do not transmit their readings in a centrally pre-defined sequence. Instead, they are divided into clusters. The computation occurs over two stages. In the first stage, the nodes contend with each other using a decentralized timer scheme to transmit their reading to their cluster heads. In the second stage, the cluster heads contend in a similar manner. The main challenge that arises with the use of the timer scheme is the possibility of collisions, which can make the algorithm fail in finding the maximum. 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 it due to collisions. Extensive benchmarking shows that TMC requires lower selection times and far fewer transmissions on average than other 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负责该传感器的传感器是很重要的。在文献中这被称为最大函数计算问题。我们提出了一种新颖的,分散的,基于计时器的最大函数计算(TMC)算法。在其中,传感器不会按中央预先定义的顺序传输其读数。而是将它们分为几类。计算分两个阶段进行。在第一阶段,节点使用分散式计时器方案相互竞争,以将其读数传输到其簇头。在第二阶段,簇头以相似的方式竞争。使用计时器方案引起的主要挑战是冲突的可能性,这可能会使算法无法找到最大值。我们优化该算法,以最大程度地减少确定最大主体所需的平均时间,该最大主体受到因碰撞而无法找到它的概率的约束。广泛的基准测试表明,与文献中提出的其他方法相比,TMC平均需要更短的选择时间和更少的传输。

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