Browsing by Author "Keleher, Peter"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Ranking Search Results in Peer-to-Peer Systems(2006-01) Gopalakrishnan, Vijay; Morselli, Ruggero; Bhattacharjee, Bobby; Keleher, Peter; Srinivasan, AravindP2P deployments are a natural infrastructure for building distributed search networks. Proposed systems support locating and retrieving all results, but lack the information necessary to rank them. Users, however, are primarily interested in the most relevant, and not all possible results. Using random sampling, we extend a class of well-known information retrieval ranking algorithms such that they can be applied in this distributed setting. We analyze the overhead of our approach, and quantify exactly how our system scales with increasing number of documents, system size, document to node mapping (uniform versus non-uniform), and types of queries (rare versus popular terms). Our analysis and simulations show that a) these extensions are efficient, and can scale with little overhead to large systems, and b) the accuracy of the results obtained using distributed ranking is comparable to a centralized implementation.Item Using Content-Addressable Networks for Load Balancing in Desktop Grids(2007-03-29) Kim, Jik-Soo; Keleher, Peter; Marsh, Michael; Bhattacharjee, Bobby; Sussman, AlanDesktop grids combine Peer-to-Peer and Grid computing techniques to improve the robustness, reliability and scalability of job execution infrastructures. However, efficiently matching incoming jobs to available system resources and achieving good load balance in a fully decentralized and heterogeneous computing environment is a challenging problem. In this paper, we extend our prior work with a new decentralized algorithm for maintaining approximate global load information, and a job pushing mechanism that uses the global information to push jobs towards underutilized portions of the system. The resulting system more effectively balances load and improves overall system throughput. Through a comparative analysis of experimental results across different system configurations and job profiles, performed via simulation, we show that our system can reliably execute Grid applications on a distributed set of resources both with low cost and with good load balance.