A Fuzzy Swarm Optimized Approach for Piece Selection in Bit Torrent Like Peer to Peer Network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32804
A Fuzzy Swarm Optimized Approach for Piece Selection in Bit Torrent Like Peer to Peer Network

Authors: M. Padmavathi, R. M. Suresh

Abstract:

Every machine plays roles of client and server simultaneously in a peer-to-peer (P2P) network. Though a P2P network has many advantages over traditional client-server models regarding efficiency and fault-tolerance, it also faces additional security threats. Users/IT administrators should be aware of risks from malicious code propagation, downloaded content legality, and P2P software’s vulnerabilities. Security and preventative measures are a must to protect networks from potential sensitive information leakage and security breaches. Bit Torrent is a popular and scalable P2P file distribution mechanism which successfully distributes large files quickly and efficiently without problems for origin server. Bit Torrent achieved excellent upload utilization according to measurement studies, but it also raised many questions as regards utilization in settings, than those measuring, fairness, and Bit Torrent’s mechanisms choice. This work proposed a block selection technique using Fuzzy ACO with optimal rules selected using ACO.

Keywords: Ant Colony Optimization (ACO), Bit Torrent, Download time, Peer-to-Peer (P2P) network, Performance.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099599

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2524

References:


[1] Steinmetz, R. (2005). Peer-to-peer systems and applications (Vol. 3485). Springer-Verlag New York Incorporated.
[2] Peer-To-Peer Network. The Government of the Hong Kong Special Administrative Region.
[3] Ding, C. H., Nutanong, S., &Buyya, R. (2005). Peer-to-peer networks for content sharing. Peerto-Peer Computing: The Evolution of a Disruptive Technology, 28-65.
[4] Qiu, D., &Srikant, R. (2004). Modeling and performance analysis of BitTorrent-like peer-to-peer networks. ACM SIGCOMM Computer Communication Review,34(4), 367-378.
[5] Liu, H., Abraham, A., & Badr, Y. (2010). Neighbor selection in peer-topeer overlay networks: a swarm intelligence approach. In Pervasive Computing (pp. 405-431). Springer London.
[6] Yang, B., & Garcia-Molina, H. (2002). Improving search in peer-to-peer networks. In Distributed Computing Systems, 2002. Proceedings. 22nd International Conference on (pp. 5-14). IEEE.
[7] Hwang, K. W., Misra, V., & Rubenstein, D. S. (2008). Stored media streaming in bittorrent-like P2P networks.
[8] Bharambe, A. R., Herley, C., &Padmanabhan, V. N. (2005). Analyzing and improving BitTorrent performance. Microsoft Research, Microsoft Corporation One Microsoft Way Redmond, WA, 98052, 2005-03.
[9] Cohen, B. (2003, June). Incentives build robustness in BitTorrent. In Workshop on Economics of Peer-to-Peer systems (Vol. 6, pp. 68-72).
[10] Skevik, K. A., Goebel, V., &Plagemann, T. (2004). Analysis of bittorrent and its use for the design of a p2p based streaming protocol for a hybrid cdn. Delft University of Technology Parallel and Distributed Systems Report Series, Tech. Rep. Technical Report.
[11] Kher, S., Somani, A. K., & Gupta, R. (2005, October). Network selection using fuzzy logic. In Broadband Networks, 2005. BroadNets 2005. 2nd International Conference on (pp. 876-885). IEEE.
[12] Michlmayr, E., Pany, A., & Graf, S. (2006, September). Applying antbased multi-agent systems to query routing in distributed environments. In Intelligent Systems, 2006 3rd International IEEE Conference on (pp. 36-41). IEEE.
[13] Han, S. C., & Xia, Y. (2009). Optimal node-selection algorithm for parallel download in overlay content-distribution networks. Computer Networks, 53(9), 1480-1496.
[14] Esposito, F., Matta, I., Bera, D., &Michiardi, P. (2011). On the impact of seed scheduling in peer-to-peer networks. Computer Networks, 55(15), 3303-3317.
[15] Bonnel, N., Ménier, G., &Marteau, P. F. (2007, October). Information replication strategy in unstructured peer-to-peer networks using thematic agents. In Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on (pp. 697-702). IEEE.
[16] Pouwelse, J., Garbacki, P., Epema, D., & Sips, H. (2005). The bittorrent p2p file-sharing system: Measurements and analysis. In Peer-to-Peer Systems IV(pp. 205-216). Springer Berlin Heidelberg.
[17] Fan, X., Zhang, W., & Guan, L. A Fuzzy Algorithm of Peer Selection for P2P Streaming Media System Based on Gossip Transmission Protocol.
[18] Liao, W. C., Papadopoulos, F., &Psounis, K. (2007). Performance analysis of BitTorrent-like systems with heterogeneous users. Performance Evaluation,64(9), 876-891.
[19] Violaris, G. C., &Mavromoustakis, C. X. (2010). On the performance evaluation and analysis of the hybridised bittorrent protocol with partial mobility characteristics. arXiv preprint arXiv:1009.1708.
[20] Neumann, F., Sudholt, D., & Witt, C. Computational Complexity of Ant Colony Optimization and Its Hybridization.
[21] Mahapatra, A., &Tarasia, N. (2011). A Fuzzy Approach for Reputation Management using Voting Scheme in Bittorrent P2P Network. International Journal of Computer Science and Information Technologies, 2(2), 735-740.
[22] Mahapatra, A., &Tarasia, N. (2011). A Fuzzy Approach for Reputation Management using Voting Scheme in Bittorrent P2P Network. International Journal of Computer Science and Information Technologies, 2(2), 735-740.
[23] Kaehler, S. D. (1998). Fuzzy Logic-An Introduction. available at www. seattle robotics. org/encoder/mar98/fuz/fl_part1. html.Dorigo, M., & Gambardella, L. M. (1997). Ant colony system: A cooperative learning approach to the traveling salesman problem. Evolutionary Computation, IEEE Transactions on, 1(1), 53-66.
[24] Blum, C. (2005). Ant colony optimization: Introduction and recent trends. Physics of Life reviews, 2(4), 353-373.
[25] Bell, J. E., & McMullen, P. R. (2004). Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics, 18(1), 41-48.
[26] Dorigo, M., Birattari, M., &Stutzle, T. (2006). Ant colony optimization. Computational Intelligence Magazine, IEEE, 1(4), 28-39.
[27] Dorigo, M., & Blum, C. (2005). Ant colony optimization theory: A survey. Theoretical computer science, 344(2), 243-278.