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A QoS improvement in P2P based Wireless Mesh Network using Hybrid Swarm Intelligence
Background/Objectives: The objective of this work is to improve efficient resource sharing in a Peer to Peer based Wireless Mesh Network using Hybrid Swarm Intelligence approach. Methods/Analysis: It is difficult to maintain a stable Distributed Hash Table (DHT) in a wireless environment due to frequent node mobility, multi-hop nature, link quality etc., The QoS parameters such as Packet Delivery Ratio (PDR), End to End Delay, Network Load, No. of hops to look up etc are severely affected by node mobility when structured peer to peer algorithm such as chord is applied in a muli-hop environment like wireless mesh network. The proposed method takes link quality, End to End delay, PDR, Query response time into consideration to improve the performance of chord. We have employed meta-heuristic algorithms such as Particle Swarm Optimization (PSO), FireFly algorithm (FF), a hybrid of PSO-FF to improve the performance of chord when applied over a multi-hop environment. Findings: The simulations are conducted when nodes are static and mobile. The performance of CHORD/PSO-FF is compared with CHORD/PSO and CHORD/FF and results showed improved performance in both the cases. Applications/Improvements: This hybrid approach improved the performance of chord protocol in a wireless mesh network when nodes are static and dynamic.
Chord, FireFly Algorithm, Hybrid PSO FF, Particle Swarm Optimization, QoS Parameters, Wireless Mesh Network.
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