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Dynamic Resource Schedule Algorithm in Elastic Data Intensive Computing Cluster

Zhaolei Duan, Xueli Wu, Jianchun Li

Abstract


In order to meet the increasing processing demand of data intensive computing, an elastic data intensive computing cluster EDICC is presented. Using local resource and cloud resource at the same time, EDICC has high availability and reliability, especially when flash crowd happens. EDICC could acquire resource from cloud when system is overloaded and release unnecessary cloud resource after load down. To achieve effective resource schedule in EDICC, propose a relative performance index R, build dynamic resource schedule algorithm basing on performance index R. Experimental results show, relative performance index R could reflect system resource status accurately. Comparing with traditional data intensive computing system, elastic data intensive computing cluster EDICC using dynamic resource schedule algorithm could achieve outstanding performance and higher resource efficiency.

Keywords


Resource Schedule, Data Intensive Computing, Load Balancing, Cloud Computing.

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