An Effective Self-adaptive Load Balancing Algorithm for Peer-to-Peer Networks

Naixue Xiong, Kaihua Xu, Lilong Chen, Laurence Tianruo Yang, Yuhua Liu

Abstract: The field of parallel and distributed computing has become increasingly significant as recent advances in electronic and integrated circuit technologies. Peer-to-Peer (P2P) cloud computing networks are the largest contributor of network traffic on the Internet. Measurement plays an important role in different P2P applications, we should enhance the measurement-based optimization of P2P networking and applications. In especial, to enhance the file sharing efficiency in P2P networks while reducing the inter-domain traffic, extensive schemes are proposed and file sharing is becoming seriously concerned. However, difference in ability, free-riding behavior and high churn have caused great unbalance on load degree between high speed network nodes. This paper presents a self-adaptive load balancing algorithm, where nodes create binary tree back-up node tables for their shared hot files automatically, and transfer extra query quest connection sent originally to heavy-load nodes and to back-up nodes. The experimental results reveal our algorithm can reduce load degree of heavy-load nodes and bring ideal balance between high speed network nodes, although under high churn, it also has balance effect and lower load degree of the whole network systems.