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  • 标题:Efficient and Parallel Data Processing and Resource Allocation in the Cloud by using Nephele’s Data Processing Framework
  • 本地全文:下载
  • 作者:V.Saranya ; S.Ramya ; R.G. Suresh Kumar
  • 期刊名称:International Journal of Grid and Distributed Computing
  • 印刷版ISSN:2005-4262
  • 出版年度:2016
  • 卷号:9
  • 期号:3
  • 页码:33-40
  • DOI:10.14257/ijgdc.2016.9.3.05
  • 出版社:SERSC
  • 摘要:Cloud computing is a technology in which the Cloud Service Providers (CSP) provide many virtual servers to the users to store their information in the cloud. The faults occurring on the assignment and dismission of the virtual machines, the processing cost in the allocation of resources must also be considered. The parallel processing of the information on the virtual machines must be done effectively and in an efficient manner. A variety of systems were developed to facilitate Many Task Computing (MTC). These systems aim to hide the issues of parallelism and fault tolerant and they are used in many applications. In this paper, we introduced Nephele, a data processing framework to exploit dynamic resource provisioning offered by IaaS clouds. The performance evaluation of the virtual machines has been evaluated and the allocation and de- allocation of job tasks to the specific virtual machines has also been considered. A performance comparison with the well known data processing framework hadoop has been done. Thus this paper tells about the effective and efficient manner of processing the data by parallel processing and allocating the correct resources for the desired task. It also helps to reduce the cost of resource utilization by exploiting the dynamic resource utilization.
  • 关键词:CSP; Allocation; De-allocation; Many Task Computing; Nephele; Dynamic ; resource utilization; Hadoop; Parallel processing
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