Reliable and Stable Route Construction in Mobile Ad Hoc Networks Using R- Learning Techniques
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 2
Abstract
Mobile Ad Hoc Networks (MANETs) are types of wireless network consist of mobile nodes which are communicating each other via wireless radio links without any underlying physical infrastructure. Due to infrastructure less, node mobility, and unreliable radio links, the reliable routing is the most challenging issue in the MANET. In this paper, we proposed novel heuristic approach called Reinforcement Learning (RL) based Reliable Hybrid Multicast Routing (RL-RHMRP) which possesses ability to learn the network context and makes routing decisions in selection of neighbor nodes and route establishment process. RL-RHMRP works based on reliable intermediate node forwarding mechanism and follows Q-Learning (QL) method (one of the RL technique) with On-policy and Model-based features. Reliable Decisive Factor (RDF) is computed based on measured power level, received signal strength, mobility, and link stability of a node. Our scheme chooses the best path from mesh of paths for data transmission by considering computed sum of RDF value for both proactive and reactive MANETs region. Simulation evaluation has been done in NS-2 for various performance parameters like Packet Delivery Ratio, Jitter, End-to-end delay, and Overheads in comparison to the zone based routing protocols such as ZRP (Zone Routing Protocol) and MZRP (Multcast Zone Routing Protocol). It is observed from result and discussions section that RL-RHMRP out performs than ZRP and MZRP.
Authors and Affiliations
Gyanappa A. Walikar
Keywords
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