Grid resource management policies for load-balancing and energy-saving by vacation queuing theory

  • Authors:

  • Fei Yin;Changjun Jiang;Rong Deng;Jianjun Yuan

  • Affiliations:

  • Department of Computer Science and Engineering, Tongji University, 4800 Caoan Road, Shanghai 201804, China and The Key Laboratory of "Embedded System and Service Computing", Ministry of Education, ...;Department of Computer Science and Engineering, Tongji University, 4800 Caoan Road, Shanghai 201804, China and The Key Laboratory of "Embedded System and Service Computing", Ministry of Education, ...;Department of Computer Science and Engineering, Tongji University, 4800 Caoan Road, Shanghai 201804, China and The Key Laboratory of "Embedded System and Service Computing", Ministry of Education, ...;Department of Computer Science and Engineering, Tongji University, 4800 Caoan Road, Shanghai 201804, China and The Key Laboratory of "Embedded System and Service Computing", Ministry of Education, ...

  • Venue:
  • Computers and Electrical Engineering
  • Year:
  • 2009

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Abstract

The resource management is the central component of grid system. The analysis of the workload log file of LCG including the job arrival and the resource utilization daily cycle shows that the idle sites in the Grid are the source of load imbalance and energy waste. Here we focus on these two issues: balancing the workload by transferring jobs to idle sites at prime time to minimize the response time and maximize the resource utilization; power management by switch the idle sites to sleeping mode at non-prime time to minimize the energy consume. We form the M/G/1 queue model with server vacations, startup and closedown to analysis the performance metrics to instruct the design of load-balancing and energy-saving policies. We provide our Adaptive Receiver Initiated (ARI) load-balancing strategy and power-management policy for energy-saving. The simulation experiments prove the accuracy of our analysis and the comparisons results indicate our policies are largely suitable for large-scale heterogeneous grid environment.