Resource Allocation Method Using Scheduling Methods for Parallel Data Processing in Cloud

Provided by: International Journal of Computer Science and Information Technologies
Topic: Cloud
Format: PDF
Infrastructure as a Service (IaaS) clouds have emerged as a promising new platform for massively parallel data processing. By eliminating the need for large upfront capital expenses, operators of IaaS clouds offer their customers the unprecedented possibility to acquire access to a highly scalable pool of computing resources on a short-term basis and enable them to execute data analysis applications at a scale which has been traditionally reserved to large Internet companies and research facilities. However, despite the growing popularity of these kinds of distributed applications, the current parallel data processing frameworks, which support the creation and execution of large-scale data analysis jobs, still stem from the era of dedicated, static compute clusters and have disregarded the particular characteristics of IaaS platforms so far.

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