Abstract
Peer-to-peer (P2P) computing has emerged as an alternative model of communication and computation to client-server model. While, P2P computing may significantly increase the performance and the scalability of the whole system, they still are facing many challenges in achieving these goals. In this paper we study the problem of scheduling a large number of tasks on such systems. We propose two techniques based on heuristic approach: a Recursive Neighbour Search and an Augmented Tabu-Search technique. These techniques do not address directly the load-balancing problem since it is completely unrealistic in such large environments, but we will show that even a non-perfectly load-balanced system can behave reasonably well by taking into account the tasks’ time demands. These algorithms are compared to a well known scheduling algorithm in order validate their performance.
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Savvas, I., Kechadi, T. (2004). Performance Study of Scheduling Mechanisms for Peer-to-Peer Computing Environments. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2003. Lecture Notes in Computer Science, vol 3019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24669-5_123
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DOI: https://doi.org/10.1007/978-3-540-24669-5_123
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