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A QoS improvement in P2P based Wireless Mesh Network using Hybrid Swarm Intelligence

Affiliations

  • Jawaharlal Technological University, kakinada - 533003, Andhra Pradesh, India
  • Santhiram Engineering College, Nandyal - 518501, Andhra Pradesh, India
  • Electrinics and Communication Engineering Department, Jawaharlal Technological University, kakinada - 533003, Andhra Pradesh, India

Abstract


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.

Keywords

Chord, FireFly Algorithm, Hybrid PSO FF, Particle Swarm Optimization, QoS Parameters, Wireless Mesh Network.

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References


  • Akyildiz Ian F, Wang X, Wang W. Wireless mesh networks: a survey. Computer Networks. 2005; 445–87.
  • Muogilim OE, Loo KK, Comley R. Wireless mesh network security: A traffic engineering management approach. Journal of Network and Computer Applications. 2011; 34(2):478–91.
  • Ahmed I, Mohammed A, Alnuweiri H. On the fairness of resource allocation in wireless mesh networks: a survey. Wireless Networks. 2013; 19 (6):1451–68.
  • Chongang W, Li LB. Peer-to-Peer Overlay Networks: A Survey. The Hong Kong University of Science and Technology, Hong Kong, 2003.
  • Jaiswal V. Adaptive content replication in Peer to Peer Network. Doctoral dissertation, San Diego State University, 2012.
  • Al Asaad A, Gopalakrishnan S, Victor L. Peer to Peer File sharing over Wireless Mesh Networks. IEEE Pacific Rim Conference on Communications, Computers and Signal Processing. 2009. p. 697–702.
  • Castro M, Kassler A, Chiasserini CF, Casetti C, Korpeoglu I. Peer-to-Peer Overlay in Mobile Ad-hoc Networks. Hand book of Peer-to-Peer Networking. 2009; 1045–80.
  • Stoica I, Morris R, Liben-Nowell D, Karger DR, Kaashoek MF, Dabek F, Balakrishnan H. Chord: a scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking. 2003; 11(1):17–32.
  • Canali C, Renda ME, Santi P. Evaluating load balancing in peer-to-peer resource sharing algorithms for wireless mesh networks. 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2008. 2008 Sep. p. 603–9.
  • Murali Krishna PP, Subramanyam MV, Satyaprasad K. Performance Analysis of Chord Protocol for Peer to Peer Overlay Topology in Wireless Mesh Network. International Journal of Computer Applications. 2013; 65(13).
  • Murali KrishnaKrishna PP, Subramanyam MV, Satyaprasad K. Mesh DHT approach for efficient resource sharing in P2P based Wireless Mesh Networks. ARPN Journal of Engineering and Applied Sciences. 2015; 10 (21).
  • Dian P, Mariyam S, Sophiyati S. Particle Swarm Optimization: Technique, System and Challenges. International Journal of Computer Applications. 2011; 14 (1):0975–8887.
  • Pengjun Z, Sanyang L, Guo C. Modified Particle Swarm Optimization for Optimization Problems. Journal of Theoritical and Applied Information Technology. 2012; 46(2):610–4.
  • Yang X-S, He X. Firefly Algorithm: Recent Advances and Applications. Int J Swarm Intelligence. 2003; 1(1):36–50.
  • Farahani SM, Abshouri AA, Nasiri B, Meybodi MR. Some hybrid models to improve firefly algorithm performance. International Journal of Artificial Intelligence. 2012; 8(12):97–117.
  • Padmavathi K, Ramakrishna KS. Hybrid Firefly and Particle Swarm Optimization algorithm for the detection of Bundle Branch Block. International Journal of the Cardiovascular Academy, International Journal of the Cardiovascular Academy. 2015.

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