Query-Trail-Mediated Cooperative Behaviors of Peers in Unstructured P2P File Sharing Networks

We propose two types of autonomic and distributed cooperative behaviors of peers for peer-to-peer (P2P) file-sharing networks. Cooperative behaviors of peers are mediated by query trails, and allows the exploration of better trade-off points between file search and storage load balancing performance. Query trails represent previous successful search paths and indicate which peers contributed to previous file searches and were at the same time exposed to the storage load. The first type of cooperative behavior is to determine the locations of replicas of files through the medium of query trails. Placement of replicas of files on strong query trails contributes to improvement of search performance, but a heavy load is generated due to writing files in storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing between peers, while avoiding significant degradation of the search performance by creating replicas of files in peers adjacent to peers on strong query trails. The second type of cooperative behavior is to determine whether peers provide requested files through the medium of query trails. Provision of files by peers holding requested files on strong query trails contributes to better search performance, but such provision of files generates a heavy load for reading files from storage to peers on the strong query trails. Therefore, we attempt to achieve storage load balancing while making only small sacrifices in search performance by having peers on strong query trails refuse to provide files. Simulation results show that the first type of cooperative behavior provides equal or improved ability to explore trade-off points between storage load balancing and search performance in a static and nearly homogeneous P2P environment, without the need for fine tuning parameter values, compared to replication methods that require fine tuning of their parameters values. In addition, the combination of the second type and the first type of cooperative behavior yields better storage load balancing performance with little degradation of search performance. Moreover, even in a dynamic and heterogeneous P2P environment, the two types of cooperative behaviors yield good ability to explore trade-off points between storage load balancing and search performance.

[1]  Edith Cohen,et al.  Search and replication in unstructured peer-to-peer networks , 2002, ICS '02.

[2]  Hiroshi Yamamoto,et al.  Storage load balancing via local interactions among peers in unstructured P2P networks , 2006, InfoScale '06.

[3]  Evangelos Pournaras,et al.  Load-driven neighbourhood reconfiguration of Gnutella overlay , 2008, Comput. Commun..

[4]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[5]  Ian T. Foster,et al.  Mapping the Gnutella Network , 2002, IEEE Internet Comput..

[6]  Sabu M. Thampi,et al.  Review of Replication Schemes for Unstructured P2P Networks , 2009, ArXiv.

[7]  Mudhakar Srivatsa,et al.  Large Scaling Unstructured Peer-to-Peer Networks with Heterogeneity-Aware Topology and Routing , 2006, IEEE Transactions on Parallel and Distributed Systems.

[8]  Lada A. Adamic,et al.  The Nature of Markets in the World Wide Web , 1999 .

[9]  Robert Morris,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM 2001.

[10]  Marco Dorigo,et al.  Mobile agents for adaptive routing , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[11]  Raj Jain,et al.  Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks , 1989, Comput. Networks.

[12]  Konstantinos Psounis,et al.  Performance analysis of BitTorrent-like systems with heterogeneous users , 2007, Performance evaluation (Print).

[13]  Letian Rong Multimedia Resource Replication Strategy for a Pervasive Peer-to-Peer Environment , 2008, J. Comput..

[14]  Daniel Stutzbach,et al.  Characterizing unstructured overlay topologies in modern P2P file-sharing systems , 2008, TNET.

[15]  Vana Kalogeraki,et al.  A fair resource allocation algorithm for peer-to-peer overlays , 2005, INFOCOM.

[16]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[17]  Edith Cohen,et al.  Replication strategies in unstructured peer-to-peer networks , 2002, SIGCOMM.

[18]  Mark Handley,et al.  A scalable content-addressable network , 2001, SIGCOMM '01.

[19]  Lifeng Sun,et al.  Understanding the Power of Pull-Based Streaming Protocol: Can We Do Better? , 2007, IEEE Journal on Selected Areas in Communications.

[20]  Hiroshi Yamamoto,et al.  Replication Methods for Load Balancing on Distributed Storagesin P2P Networks , 2006, IEICE Trans. Inf. Syst..

[21]  Jon Crowcroft,et al.  A survey and comparison of peer-to-peer overlay network schemes , 2005, IEEE Communications Surveys & Tutorials.

[22]  Antony I. T. Rowstron,et al.  Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems , 2001, Middleware.

[23]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[24]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[25]  Rajeev Motwani,et al.  Randomized algorithms , 1996, CSUR.

[26]  Donald F. Towsley,et al.  On distinguishing between Internet power law topology generators , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[27]  Albert,et al.  Topology of evolving networks: local events and universality , 2000, Physical review letters.

[28]  Fabián E. Bustamante,et al.  Taming the torrent: a practical approach to reducing cross-isp traffic in peer-to-peer systems , 2008, SIGCOMM '08.

[29]  Do Young Eun,et al.  Minimizing file download time in stochastic peer-to-peer networks , 2008, TNET.