Established Link Optimization using Particle Swarm Optimization Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-36 Number-1
Year of Publication : 2016
Authors : P.Karpagavalli, R.Selvaraj
  10.14445/22312803/IJCTT-V36P107

MLA

P.Karpagavalli, R.Selvaraj "Established Link Optimization using Particle Swarm Optimization Algorithm". International Journal of Computer Trends and Technology (IJCTT) V36(1):38-42, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In modern days, various techniques have been proposed to improve overlay network performances. The quality of services is obtained in the overlay network through selection of best links. In previous researches are suggested several methods but has failed to provide optimal links between source and destination nodes. In the existing system, various factors that can affect the performance of overlay network routing, multi-goal optimization model for overlay link selection problem can be put forward. This scenario model assumes the factor of the physical link reuse, and it strives to preserve a greater performance of the overlay routing. But it affects the overlay network performances and hence we go for proposed scenario. In the proposed system, we introduce particle swarm optimization (PSO) which is used to improve the link optimization in overlay network. It preserves the higher performance of overlay routing in less expensive. The resources are allocated sufficiently in the network and it is reusable for number of times hence the utilization is increased. The minimum path is computed between nodes and optimal links are updated in the specified network. The links are optimally improved and hence the overhead communication issue is reduced significantly. From the experimental result, we can conclude that the proposed method is better than the existing system.

References
[1] ClaudiuDanilov. "Performance and functionality in overlay networks." PhD diss., Ph. D. thesis, Department of Computer Science, Johns Hopkins University, 2004.
[2] Dave Clark, Bill Lehr, Steve Bauer, PeymanFaratin, Rahul Sami, and John Wroclawski. "Overlay Networks and the Future of the Internet."Communications and Strategies 63 (2006): 109.
[3] Antonio Capone, Jocelyne Elias, and Fabio Martignon. "Models and algorithms for the design of service overlay networks." Network and Service Management, IEEE Transactions on 5, no. 3 (2008): 143-156.
[4] SeungChulHan, and Ye Xia. "Optimal Node Selection Algorithm for Parallel Access in Overlay Networks."
[5] ChipingTang, and Philip K. McKinley. "Improving multipath reliability in topology-aware overlay networks." In Distributed Computing Systems Workshops, 2005. 25th IEEE International Conference on, pp. 82-88. IEEE, 2005.
[6] Peter Pietzuch, Jeffrey Shneidman, Matt Welsh, Margo Seltzer, and MemaRoussopoulos. "Path optimization in stream-based overlay networks." Tr, Harvard University (2004).
[7] Ferretti, Stefano, Searching in Unstructured Overlays Using Local Knowledge and Gossip, Complex Networks V. Springer International Publishing, 2014. 63-74.
[8] Yang, Jing, Based on the Genetic Algorithm to Optimize the QoS Routing Algorithm, International Journal of Future Generation Communication and Networking 7.4 (2014): 195-204.
[9] Al Ridhawi, Yousif, and Ahmed Karmouch, QoS-Based Composition of Service Specific Overlay Networks, Computers, IEEE Transactions on 64.3 (2015): 832-846.
[10] Chen, Zhe, Pingyi Fan, and KhaledLetaief, Computeand- forward: optimization over multi-source-multi-relay networks (2014).
[11] Kalambe, K. D., A. R. Deshmukh, and S. S. Dorle, Particle Swarm Optimization based Routing Protocol for Vehicular Ad Hoc Network.
[12] Lin, Cheng-Jian, Cheng-Hung Chen, and Chin-Teng Lin, A hybrid of cooperative particle swarm optimization and cultural algorithm for neural fuzzy networks and its prediction applications, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on 39.1 (2009): 55-68.

Keywords
Link selection, particle swarm optimization algorithm, overlay network, bandwidth, overlay degree.