Self‐Organized Formation and Evolution of Peer‐to‐Peer Networks

Self‐Organized Formation and Evolution of Peer‐to‐Peer Networks

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Article ID: iaor20134948
Volume: 25
Issue: 3
Start Page Number: 502
End Page Number: 516
Publication Date: Jun 2013
Journal: INFORMS Journal on Computing
Authors: , ,
Keywords: distributed computer systems, social networks
Abstract:

Peer‐to‐peer (P2P) networks are social networks for pooling network and information resources and are considered superior conduits for distributed computing and data management. In this paper, we utilize the theories of social networks and economic incentives to investigate the formation of P2P networks with rational participating agents (active peers). The paper proposes a framework for multilevel formation dynamics, including an individual level (content‐sharing decision and group selection) and a group level (membership admission, splitting, and interconnection). It is found that if the network size (the number of peer nodes) is sufficiently large, the stable (self‐selected equilibrium) free‐riding ratio could be nonzero, contrary to the common belief that everybody should free ride. The efficient (welfare‐maximizing) free‐riding ratio is not necessarily zero; that is, a certain degree of free riding is beneficial and should be tolerated. The sharing level in a network increases (decreases) with the download (upload) capacities of its peer nodes. In addition, the heterogeneity of content availability and upload capacity discourages sharing activities. Although the sharing level of a stable group is typically lower than that of an efficient group, the self‐formed network may have a larger or smaller group size than what is efficient, depending on the structure of the group admission decision process. It is also observed that self‐organized interconnections among groups lead to network inefficiency because the network may be over‐ or underlinked. To recover the efficiency loss during the formation process, we propose internal transfer mechanisms to force stable networks to become efficient.

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