Kai Shuang

An Efficient Search Mechanism in Unstructured P2P Networks Based on Semantic Group

Recently among various searching techniques, semantic-based searching has drawn significant attention. In this paper, we propose a novel and efficient search mechanism BF-SKIP (Biased walk, Flooding and Search with K-Iteration Preference). We use Vector Space Model (VSM) and relevance ranking algorithms to construct the overlay network. In BF-SKIP system, the search mechanism is divided into three stages (A, B and C). It significantly reduces the number of redundant messages and the number of visited nodes. Our analysis and simulation results show that the BF-SKIP scheme can outperform GES in terms of higher precision and lower search cost.

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.

Cowtra: A COntribution Willingness-Based Two-phase Bandwidth Resource Allocation Algorithm in P2P Network

Free-riding phenomenon is overwhelming in nowadays p2p network which causes researchers to investigate and develop many approaches to combat it. However, almost all the studies neglect the role of relative contribution of peers, namely willingness of contribution (WoC) in our paper. The ignorant to the ratio of peer’s actually contribution to its physical capability would undoubtedly lead to unfairly resource allocation and discourage many peers, as well as loose their support in long term Therefore, in this paper we present a novel and effective approach Cowtra to address such problem. Our algorithm guarantees that the bandwidth of a source node is distributed properly according to the absolute contribution of the competing peers. Then we adjust the amount of competing peers’ received bandwidth by utilizing the WoC in the second phase, such that peers with higher WoC obtain more resource while peers with lower WoC otherwise. At last, simulation results demonstrate the superiority of our algorithm in terms of fairness and efficiency.