Abstract
Decentralized peer-to-peer (P2P) networks (lacking a GRID-style resource management and scheduling infrastructure) are an increasingly important computing platform. So far, little is known about the scaling and reliability of optimization algorithms in P2P environments. In this paper we present empirical results comparing two P2P algorithms for real-valued search spaces in large-scale and unreliable networks. Some interesting, and perhaps counter-intuitive findings are presented: for example, failures in the network can in fact significantly improve performance under some conditions. The two algorithms that are compared are a known distributed particle swarm optimization (PSO) algorithm and a novel P2P branch-and-bound (B&B) algorithm based on interval arithmetic. Although our B&B algorithm is not a black-box heuristic, the PSO algorithm is competitive in certain cases, in particular, in larger networks. Comparing two rather different paradigms for solving the same problem gives a better characterization of the limits and possibilities of optimization in P2P networks.
Full length version at http://eprints.biblio.unitn.it/archive/00001541/ . This work was supported by the European Space Agency through Ariadna Project “Gossip-based strategies in global optimization” (21257/07/NL/CB). M. Jelasity was supported by the Bolyai Scholarship of the Hungarian Academy of Sciences. B. Bánhelyi was supported by the Ferenc Deák Scholarship No. DFÖ 19/2007, Aktion Österreich-Ungarn 70öu1, and OTKA T 048377.
This work was partially supported by the Future & Emerging Technologies unit of the European Commission through Project CASCADAS (IST-027807).
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Bánhelyi, B., Biazzini, M., Montresor, A., Jelasity, M. (2009). Peer-to-Peer Optimization in Large Unreliable Networks with Branch-and-Bound and Particle Swarms . In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_10
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DOI: https://doi.org/10.1007/978-3-642-01129-0_10
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