Quick, decentralized, one-shot max function computation using timer-based selection

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.