Energy enhancement of routing protocol with hidden Markov model in wireless sensor networks

Energy enhancement is a crucial factor while designing routing models in wireless sensor networks (WSNs). Many energy efficiency routing schemes are implemented to exchange various forms of gathered data by sensors in an optimal routing path through the network to increase its lifespan and maintain high scalability of the WSN. In this paper, a stochastic energy enhancement routing model is proposed to reduce the resource usage by nodes during the routing process. We aim to adapt the stochastic formalism based on the hidden Markov models (HMM) to learn from existing sensor networks, and design a new optimal routing mechanism that significantly exploits the available resources. Meanwhile, the proposed stochastic routing algorithm performs overall energy reduction in the network and permits optimal data transmission. The experimental results show that the proposed technique is efficient in terms of energy consumption, overall resource enhancement, and permits to increase network lifetime at least 19.05% compared to other existing methods.