本研究將信譽管理機制加入粒子群最佳化演算中，讓使用者能搜尋出最近與信譽較佳之地方下載所需之檔案，本研究主要目的有：(1)使用Round-trip time (RTT)求出使用者之間的距離，Peer-to-peer使用者可藉由鄰近點下載檔案。(2)將信譽管理(Reputation)機制加入粒子群最佳化演算法(Particle Swarm Optimization, PSO)，利用粒子與貢獻度尋找最適下載點；本機制可幫助P2P系統，對於需求者提出的下載需求，可藉此降低搭便車行為與減少惡意使用者的存在。
現行P2P系統有部份的檔案提供者會分享惡意檔案，於是為了實現讓P2P的需求者在下載時可以避免下載到惡意檔案。本研究擬將信譽管理機制加入到P2P系統裡，並使用PSO演算法處理需求者提出的需求，讓粒子可依據檔案提供者的貢獻度高低，進而幫助需求者尋找出最適合的下載對象。
對於需求者而言，必須於檔案下載完成後對檔案提供者進行回饋評分，本研究機制會依據使用者之間的上傳、下載及回饋值，進一步更新雙方的貢獻度。
利用本研究方法之信譽管理及透過粒子群演算法尋找最適合的下載對象，經過實驗證明，本研究提出的方法確實有效提升使用者分享意願及降低搭便車行為。

The Reputation Management system will be added in Particle Swarm Optimization Algorithm, allowing users to search for a better and credibility file to download. The main purposes of this study are: (1) the use of Round-trip time (RTT) to find the distance between the user, P2P users can download files through the neighborhood. (2) Through the contribution and particle to search for optimal user to download. This mechanism can useful the P2P system, proposed for the needs of those who download the needs of can be reduced free-riding behavior and malicious users.
Most P2P file system exist malicious file, so in order to achieve the user can avoid downloading malicious files. This study used reputation management system and PSO algorithm to help those who need to download to find out the "Good" user to download.

[1] A. Abraham, H. Liu, and T. Chang, “Variable Neighborhood Particle Swarm Optimization Algorithm,” Genetic and Evolutionary Computation Conference, 2006.
[2] F. H. P. Fitzek, and H. Charaf, “Mobile peer to peer,” A John Wiley and Sons, Ltd., Publication, 2009.
[3] F. Y. Shih, and Y.-T. Wu, “Fast Euclidean distance transformation in two scans using a 3x3 neighborhood,” Computer Vision and Image Understanding, Vol. 93, pp. 195-205, 2004.
[4] F. Y. Shih, and Y.-T. Wu, “Three-dimensional Euclidean distance transformation and its application to shortest path planning,” Pattern Recognition, Vol. 37, pp. 79-92, 2004.
[5] I. Stoica, R. Morris, D. Karger, M. F. Kaashoek, and H. Balakrishnan, “Chord: A scalable peer-to-peer lookup service for Internet applications,” ACM SIGCOMM, Rev. 31, 4 , pp. 149-160, 2001.
[6] J. Cates, “Robust and Efficient Data Management for a Distributed Hash Table,” Master's thesis, Massachusetts Institute of Technology, 2003.
[7] J. Kennedy, and R. C. Eberhart, “Particle Swarm Optimization,” In Proceedings of the Fourth IEEE International Conference on Neural Networks, 1995, Vol. 4, pp. 1942-1948.
[8] J. Golbeck, and J.A. Hendler, “Reputation Network Analysis for Email Filtering,” in Proc. of the First Conference on Email and Anti-Spam, 2005.
[9] J. Golbeck, and J. Hendler, “FilmTrust: Movie recommendations using trust in web-based social networks,” Proc. of the IEEE Consumer Communications and Networking Conference, January 2006.
[10] J. Kennedy, and R. C. Eberhart, “Swarm Intelligence,” Morgan Kaufmann, 2001.
[11] J. Wang, R. Shen, C. Ullrich, H. Luo, and C. Niu, “Resisting free-riding behavior in BitTorrent,” Future Generation Computer Systems, Vol. 26(8), pp. 1285-1299, 2010.
[12] L. Mekouar, Y. Iraqi, and R. Boutaba, “A Reputation Management and Selection Advisor Schemes for Peer-to-Peer Systems,” In Proc. the 15th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management, 2004, pp.208-219.
[13] L. Mekouar, Y. Iraqi, R. Boutaba “Peer-to-peer’s most wanted: Malicious peers”, Computer Networks: The International Journal of Computer and Telecommunications Networking, Vol. 50, pp. 545-562, 2006.
[14] L. Xiong, and L. Liu, “PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities,” IEEE Trans. Knowl. Data Eng., Vol. 16(7), 2004, pp. 843-857.
[15] M. Feldman, and J. Chuang, “Overcoming free-riding behavior in peer-to-peer systems,” ACM SIGecom Exchanges, Vol 5(4), pp. 45-50, 2005.
[16] M. Karakaya, İ. Körpeoğlu and Ö. Ulusoy, “Counteracting free riding in Peer-to-Peer networks,” Computer Networks, Vol. 52(3), pp. 675-694, 2008.
[17] N. Fedotova, L. Veltri, “Reputation management algorithms for DHT-based peer-to-peer environment,” Computer Communications archive, Vol. 32 pp. 1400-1409, 2009
[18] N. Mladenovic, P. Hansen “Variable Neighborhood Search,” European Journal of Operational Research, Vol. 191, Issue 3, pp. 593-595, 2008.
[19] P. Anderson, “BOINC: A System for Public-Resource Computing and Storage,” IEEE/ACM International Workshop on Grid Computing, 2004, pp. 4-10.
[20] S. Sun, A. Abraham, G. Zhang, H. Liu “A Particle Swarm Optimization Algorithm for Neighbor Selection in Peer-to-Peer Networks,” IEEE Computer Society, pp. 166-172, 2007
[21] S. Marti, and H. Garcia-Molina, “Taxonomy of Trust: Categorizing P2P Reputation Systems,” Computer Networks: The International Journal of Computer and Telecommunications Networking, Vol. 50, pp. 472-484, 2006.
[22] Z. Despotovic, K. Aberer, “P2P reputation management: Probabilistic estimation vs. social networks,” Computer Networks: The International Journal of Computer and Telecommunications Networking, Vol. 50, pp. 485-500, 2006.
[23] H. Balakrishnan, M. Frans Kaashoek, D. Karger, R. Morris, and I. Stoica, “Looking up data in P2P systems,” Communications of the ACM, Vol. 46(2), pp. 43-48, 2003.