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


In several wireless sensor networks, it's of interest to see the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-primarily based, one-shot max perform computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in an exceedingly centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two competition stages. Initial, the nodes in each cluster contend with every alternative using the timer theme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the very best sensor reading in their cluster to the fusion node. One new challenge is that the utilization of the timer theme leads to collisions, that can build the algorithm fail. We have a tendency to optimize the algorithm to reduce the common time required to see the most subject to a constraint on the chance that it fails to search out the most. TMC considerably lowers average function computation time, average range of transmissions, and average energy consumption compared to approaches proposed within the literature.

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