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A Distributed Job Scheduler Virtual Machine-based Data Centres


K.SUSEELA , RatnaVel Subramaniam College of Engineering & Technology; Mr. T.VINOTH KUMAR M.E., M.B.A., Assistant Professor, RatnaVel Subramaniam College of Engineering & Technology


Data centre, virtual machines, on-demand resource allocation, optimization, algorithm, model


The existing techniques by turning on or off servers with the help of virtual machine (shortly called as VM) migration are not enough. Instead, finding an optimized dynamic resource allocation method to solve the problem of on-demand resource provision for VMs is the key to improve the efficiency of data centers. However, the existing dynamic resource allocation methods only focus on either the local optimization within a server or central global optimization, limiting the efficiency of data centers. A two-tiered on-demand resource allocation mechanism consisting of the local and global resource allocation with feedback to provide on-demand capacities to the concurrent applications. On-demand resource allocation using optimization theory based on the proposed dynamic resource allocation mechanism and model, It propose a set of on-demand resource allocation algorithms. This algorithm preferentially ensures performance of critical applications named by the data center manager when resource competition arises according to the time-varying capacity demands and the quality of applications. Using Rainbow, a Xen-based prototype implemented, it evaluates the VM-based shared platform as well as the two-tiered on-demand resource allocation mechanism and algorithms. The experimental results show that Rainbow without dynamic resource allocation (Rainbow-NDA) provides twenty six to three twenty four percent improvements in the application performance, as well as twenty six percent higher average CPU utilization than traditional service computing framework, in which applications use exclusive servers. The two-tiered on-demand resource allocation further improves performance by nine to sixteen percent for those critical applications, seventy five percent of the maximum performance improvement, introducing up to five percent performance degradation to others, with one to five percent improvements in the resource utilization in comparison with Rainbow-NDA.

Other Details

Paper ID: IJSRDV2I2250
Published in: Volume : 2, Issue : 2
Publication Date: 01/05/2014
Page(s): 872-875

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