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  • 标题:Load Balancing Model for Distributed File System in Cloud Computing using Distributed Hash Table Approach
  • 本地全文:下载
  • 作者:Ms. Arpita M. Hirudkar ; Dr.V.M.Thakare ; Dr. R.V Dharaskar
  • 期刊名称:International Journal of Electronics, Communication and Soft Computing Science and Engineering
  • 印刷版ISSN:2277-9477
  • 出版年度:2014
  • 卷号:3
  • 期号:Special
  • 出版社:IJECSCSE
  • 摘要:Load balancing in the cloud computing environmenthas an important impact on the performance. Good loadbalancing makes cloud computing more efficient and improvesuser satisfaction. The Cloud has become a popular data storageprovider and users are relying heavily on it to keep their data.Furthermore, most cloud data servers replicate their data storageinfrastructures and servers at various sites to meet the overallhigh demands of their clients and increase availability. Thetechnique, Dual-Direction FTP utilizes the availability ofreplicated files on distributed servers to enhance file downloadtimes through concurrent downloads of file blocks from oppositedirections in the files. Distributed file systems are key buildingblocks for cloud computing applications. In such file systems,nodes simultaneously serve computing and storage functions; afile is partitioned into a number of chunks allocated in distinctnodes. The load rebalancing issue in distributed file systemsspecialized for large-scale, dynamic and data-intensive clouds.Files can also be dynamically created, deleted, and appended.This results in load imbalance in a distributed file system; that is,the file chunks are not distributed as uniformly as possible amongthe nodes. A fully distributed load rebalancing algorithm is usedto solve the load imbalance problem. The main aim of proposeddynamic load balancing technique for the distributed file systemis to reallocate file blocks such that the blocks can be distributedto the system as uniformly as possible while reducing themovement cost as much as possible and to enhance downloadspeed and reduce the concurrent transfer overhead
  • 关键词:cloud computing; load balancing; DHT
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