Title :
An Effective Self-adaptive Load Balancing Algorithm for Peer-to-Peer Networks
Author :
Xiong, Naixue ; Xu, Kaihua ; Chen, Lilong ; Yang, Laurence T. ; Liu, Yuhua
Author_Institution :
Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China
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.
Keywords :
cloud computing; parallel processing; peer-to-peer computing; resource allocation; telecommunication traffic; trees (mathematics); Internet; P2P cloud computing networks; automatic hot file sharing; binary tree back-up node tables; churn rate; distributed computing; file sharing efficiency enhancement; free-riding behavior; heavy-load nodes; high-speed network nodes; inter-domain traffic reduction; load degree reduction; measurement-based optimization; parallel computing; peer-to-peer networks; query quest transfer connection; self-adaptive load balancing algorithm; Algorithm design and analysis; Economics; Educational institutions; Entropy; Load management; Load modeling; Peer to peer computing; Load Balancing; Network Structural Entropy; Peer-to-Peer; Self-adaptibility;
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0974-5
DOI :
10.1109/IPDPSW.2012.179