Topology control game algorithm based on Markov lifetime prediction model for wireless sensor network

X Hao, L Wang, N Yao, D Geng, B Chen - Ad Hoc Networks, 2018 - Elsevier
X Hao, L Wang, N Yao, D Geng, B Chen
Ad Hoc Networks, 2018Elsevier
Since the wireless sensor network (WSN) consists of large number of sensors with limited
energy resource, how to prolong the network lifetime is an inherent problem in wireless
sensor network topology control. Motivated with this problem, we present a novel Markov
lifetime prediction model (MLPM) for each single node to forecast their lifetime from a mode
transition perspective. MLPM realizes the real-time prediction of node lifetime until the node
died. Besides, on the basis of this model, this paper proposes TCAMLPM, a distributed …
Abstract
Since the wireless sensor network (WSN) consists of large number of sensors with limited energy resource, how to prolong the network lifetime is an inherent problem in wireless sensor network topology control. Motivated with this problem, we present a novel Markov lifetime prediction model (MLPM) for each single node to forecast their lifetime from a mode transition perspective. MLPM realizes the real-time prediction of node lifetime until the node died. Besides, on the basis of this model, this paper proposes TCAMLPM, a distributed topology control game algorithm for WSN which ensures the algorithm to converge to Nash Equilibrium by making use of the best response strategy. With TCAMLPM, energy conservation is accomplished by adjusting transmitting power of the nodes. The comparison results of our algorithm with the other algorithm that also aims at maximizing the network lifetime show that TCAMLPM not only extends the network lifetime, but also performs better in guaranteeing the network connectivity and robustness.
Elsevier
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