Implementing Bottleneck Detection Algorithm in IaaS Cloud for Parallel Data Processing Using Nephele

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Provided by: IJCSMR
Topic: Cloud
Format: PDF
In recent years ad-hoc parallel data processing has emerged to be one of the killer applications for Infrastructure-as-a-Service (IaaS) clouds. However, the processing frameworks which are currently used have been designed for static, homogeneous cluster setups and disregard the particular nature of a cloud. In this paper, the author starts discussing the opportunities and challenges for efficient parallel data processing in clouds. It is the first data processing framework to explicitly exploit the dynamic resource allocation offered by today's IaaS clouds for both, task scheduling and execution.
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