Selfish neighbor selection in peer-to-peer backup and storage applications

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Abstract

In this work we tackle the problem of on-line backup with a peer-to-peer approach. In contrast to current peer-to-peer architectures that build upon distributed hash-tables, we investigate whether an uncoordinated approach to data placement would prove effective in providing embedded incentives for users to offer local resources to the system. By modeling peers as selfish entities striving for minimizing their cost in participating to the system, we analyze equilibrium topologies that materialize from the process of peer selection, whereby peers establish bi-lateral links that involve storing data in a symmetric way. System stratification, that is the emergence of clusters gathering peers with similar contribution efforts, is an essential outcome of the peer selection process: peers are lured to improve the "quality" of local resources they provide to access clusters with lower operational costs. Our results are corroborated by a numerical evaluation of the system that builds upon a polynomial-time best-response algorithm to the selfish neighbor selection game. © 2009 Springer.

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APA

Michiardi, P., & Toka, L. (2009). Selfish neighbor selection in peer-to-peer backup and storage applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5704 LNCS, pp. 548–560). https://doi.org/10.1007/978-3-642-03869-3_52

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