Title :
A MANET routing protocol using Q-learning method integrated with Bayesian network
Author :
Ke Wang ; Wai-Choong Wong ; Teck Yoong Chai
Author_Institution :
NUS Grad. Sch. for Integrative Sci. & Eng., Nat. Univ. of Singapore, Singapore, Singapore
Abstract :
Frequent changes in topology and link quality in mobile ad-hoc networks (MANETs) present challenging problems in achieving optimal performance. We propose a self-learning routing protocol based on Q-learning that makes use of Quality of Service (QoS) parameters such as Signal to Interference plus Noise Ratio (SINR), delay and throughput, to make routing decisions. At the same time, a Bayesian Network (BN) is implemented to estimate neighboring network congestion level to tune the Q-learning weights. Our protocol also sends out probing packets to detect and solve the routing-loop problem which is not addressed in most Q-learning-based routing proposals. The simulation results show that the proposed system demonstrates comparatively better performance in a dense heavy-loaded scenario.
Keywords :
Bayes methods; decision making; mobile ad hoc networks; quality of service; radio links; routing protocols; telecommunication network topology; Bayesian network; MANET routing protocol; Q-learning method; link quality; mobile ad-hoc network; neighboring network congestion level estimation; quality of service parameter; routing decision making; routing-loop problem; self-learning routing protocol; signal to interference plus noise ratio; topology; Bayesian methods; Delay; Interference; Routing; Routing protocols; Signal to noise ratio; Throughput;
Conference_Titel :
Communication Systems (ICCS), 2012 IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-2052-8
DOI :
10.1109/ICCS.2012.6406152