Title :
A tailored Q- Learning for routing in wireless sensor networks
Author :
Sharma, V.K. ; Shukla, S.S.P. ; Singh, V.
Author_Institution :
Dept. of Comput. Sci. & Eng., Jaypee Polytech. & Training Centre, Rewa, India
Abstract :
Wireless sensor networks (WSNs) have major importance in distributed sensing applications. The important concern in the intend of wireless sensor networks is battery consumption which usually rely on non-renewable sources of energy. In this paper we have proposed a tailored Q-Learning algorithm for routing scheme in wireless sensor network. Our primary goal is to make an efficient routing algorithm with help of modified Q-Learning approach to minimize the energy consumption utilized by sensor nodes. This approach is a modified version of existing Q-Learning method for WSN that leads to the convergence problem.
Keywords :
learning (artificial intelligence); telecommunication computing; telecommunication network routing; wireless sensor networks; Q- learning; Q-learning algorithm; WSN; battery consumption; distributed sensing applications; energy consumption; modified Q-learning approach; nonrenewable energy sources; routing algorithm; routing scheme; sensor nodes; wireless sensor network routing; Artificial neural networks; Lead; Wireless sensor networks; Convergence Problem; Q-Learning; Reinforcement learning; WSN Flooding Routing Protocol;
Conference_Titel :
Parallel Distributed and Grid Computing (PDGC), 2012 2nd IEEE International Conference on
Conference_Location :
Solan
Print_ISBN :
978-1-4673-2922-4
DOI :
10.1109/PDGC.2012.6449899
