Prolonging network lifetime and energy reduction using path reputation based on monte Carlo algorithm for WSNs

This paper addresses the modified Monte Carlo algorithm to determine the best rule to distinguish between misbehaving nodes and cooperative nodes for the best proper path in wireless sensor network that satisfies the minimum energy, maximum node lifetime and guarantee high path reputation value. A topological profile has been designed by static nodes which are separated be two types such as sensor nodes and actor nodes. The actors are stationed and positioned at reachable spots on the land alongside the river whereas sensor nodes are floating in the river. The topology has been motivated from a segmentised of the real physical terrain of arterial river in Thailand, namely, Chaophraya. By that, the system has been formulated as the semi-Markov decision process. Moreover, to evaluate the system performance, three objective functions have been proposed which are the minimisation of energy consumption, the maximisation of node lifetime and the path reputation. Through preliminary simulations, the reported results show that the Monte Carlo algorithm with the proposed path reputation scheme outperforms both uniform and greedy selections. Moreover, our proposed method can also increase by up to 10.22% on average comparing with the other two methods. The path reputation scheme is finally confirmed its capability in promoting the reliably path by incorporating the good node behaviors.