Journal of Computer Science

A MULTI ATTRIBUTE RANKING MECHANISM FOR PEER-TO-PEER NETWORKS

B. Swaminathan and Sheila Anand

DOI : 10.3844/jcssp.2014.1458.1465

Journal of Computer Science

Volume 10, Issue 8

Pages 1458-1465

Abstract

P2P systems are envisioned to play a greater role in collaborative applications. P2P environments remove the challenging task of using servers for information sharing. Emerging collaborative P2P systems require discovery and utilization of multi-attribute, distributed and dynamic group of resources to achieve greater tasks beyond conventional file and processor cycle sharing. The process of selection of a peer for collaborative work therefore plays a significant role in accomplishing the task. Collaborative P2P systems use a group of diverse resources like hardware, software, services and data to accomplish the task or application. Hence, ranking of peers based on multiple heterogeneous attributes plays a significant role in enabling the selection of the right peers for collaboration. This study proposes the use of Analytic Hierarchy Process (AHP) for ranking the peers for selection. The relative importance of the attributes has to be decided based on the P2P application that is being collaborated. AHP provides the mathematical technique for decision making for ranking the peers for collaborative activity. The application of AHP for peer ranking has been illustrated with the use of examples. The system has been implemented and tested using Planet Lab dataset. The selection of right peer using this method has improved the process of multi attribute decision making and an optimal decision has been obtained by mapping the requirements to the available resources. The number of criteria used for P2P collaboration has been varied and the results observed shows that the decision making time increases proportional to the number of criteria.

Copyright

© 2014 B. Swaminathan and Sheila Anand. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.