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

  • Authors:

  • Yung-Ming Li;Yong Tan;Prabuddha De

  • Affiliations:

  • Institute of Information Management, National Chiao Tung University, Hsinchu, 300, Taiwan;Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195;Krannert School of Management, Purdue University, West Lafayette, Indiana 47907

  • Venue:
  • INFORMS Journal on Computing
  • Year:
  • 2013

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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.