Dynamic Coordination of Energy and Hops in WSNs Using Reinforcement Learning Routing Algorithm
Jianyong Li, Huang Wei · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2015
In wireless sensor network, the existing reinforcement learning routing algorithm usually optimize single goal and the process of route establishment is complex.It also has problem of data forwarding control overhead.In this paper, we present a dynamic adaptive routing algorithm with feedback learning ability to balance the energy of wireless sensor network, to reduce the routing hops, and to reduce the establishment complexity.The algorithm will use the local routing information and the method of feedback to learn neighbors' state; routing reward values will be obtained by weighted calculation according to the energy information and the hop counts information; the optimal routing strategy will be obtained by updating the Q-value of routing table.