TARC: A Novel Topology Adaptation Algorithm Based on Reciprocal Contribution in Unstructured P2P Networks

The autonomous behaviors of peers are usually neglected in the topology formation and adaptation in P2P network, thus a large number of Free-rider and Malicious peers would reside in the center of network, which degrades the user perceived QoE and overall network performance. In this paper, a novel and fully distributed approach Topology Adaptation algorithm based on Reciprocal Contribution (TARC) is proposed to address such problem. In our paradigm, the topology would be periodical optimized according to Reciprocal Contribution Capacity (RCC) of peers. The RCC reflects the historical behavior of a peer with regard to its content provision and transmission capability as well as nodes locating capability. Peer that possesses higher RCC, namely contributor, as it were more cooperative would be easily and likely to establish connections with others. On the other hand, malicious and free-riding nodes would be recognized and forced to the marginal of P2P network. It is shown through experiments that TARC effectively suppress the fake services and prevent non-contribution peer from occupying the center of network. What´s more, there is a significant improvement in term of overall search quality and downloading time, for contributing peers in a network that applies our algorithm.