DocumentCode :
3539681
Title :
A file replication method based on demand forecasting in P2P networks
Author :
Kageyama, Jun ; Kobayashi, Mamoru ; Shibusawa, Susumu ; Yonekura, Tatsuhiro
Author_Institution :
Grad. Sch. of Sci. & Eng., Ibaraki Univ., Hitachi, Japan
fYear :
2009
fDate :
4-6 Aug. 2009
Firstpage :
268
Lastpage :
274
Abstract :
In peer-to-peer (P2P) networks that support file-sharing services, the level of access demand can vary widely between different files. Since fewer nodes store files for which there is a lower demand, these files are more likely to be lost from the P2P networks if the users leave the network or delete the files. The loss of files can cause users to seek alternatives to P2P services, and leads to the degradation in service quality. In this study we propose and evaluate a replication method considering a service quality that aims to prevent the loss of low-demand files. In this method, the number of file replicas to be placed is determined based on the forecast demand for the file, so that the loss of low-demand files is likely to be prevented by placing replicas at nodes that frequently use P2P services. Based on the result of a simulation, we compared our proposed method with basic replication methods in terms of the amount of storage used, and the number of files. Our experimental results show that the proposed method prevents the loss of files by preserving low-demand files over extended periods of time. We also confirmed that the node storage resources consumed by this method are efficiently used.
Keywords :
demand forecasting; peer-to-peer computing; demand forecasting; file replication method; peer-to-peer network; service quality; Decision support systems; Demand forecasting; Virtual reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the
Conference_Location :
London
Print_ISBN :
978-1-4244-4456-4
Electronic_ISBN :
978-1-4244-4457-1
Type :
conf
DOI :
10.1109/ICADIWT.2009.5273909
Filename :
5273909
Link To Document :
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