P2P systems are nowadays being used not only for file sharing but also for developing large-scale distributed applications. As an emerging paradigm for distributed computing, P2P systems are raising important issues as many novel aspects have to be dealt with in such systems. One key issue in P2P distributed computing is the efficient discovery and selection of peers, which is needed for many purposes such as efficient allocation of jobs to peers, load balancing, efficient file transfer, etc. Existing P2P distributed applications use ad hoc ways to discover and selectpeers, usually without any performance guarantee.In this paper we address the problem of the efficient peerselection in P2P distributed platforms. To this end, we havedeveloped a P2P distributed platform using Sun's JXTA technology, which is endowed with resource brokerage strategies to efficiently select peers using four selection models: (a) economic scheduling model; (b) priced-based model; (c) peer-priority selection model; and, (d) random selection model. These different models are aimedto match different needs of P2P applications. Next, we havedeployed the P2P JXTA platform in a real network using nodes of the PlaneLab --a planetary scale distributed infrastructure-- and have experimentally evaluated the performance of the peer selection models by using a distributed application for processinglarge size log files of a virtual campus, which requires bothefficient file transmission and processing in P2P nodes.The results of our work showed the need to develop, implement and evaluate appropriate models for efficient peer selection to match the different requirements of large-scale P2P distributed applications. Although we have used a concrete technology such as JXTA, our approach is applicable in a more general context of P2P and Grid computing domain. Finally, our approach to peer selection through brokerage services is very flexible allowing extensions with other models

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