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Resource Selection in Grids Using Contract Net

Resource Selection in Grids Using Contract Net. Kunal Goswami, Arobinda Gupta Cisco Systems, Bangalore, India Dept. of Computer Science & Engineering and School of IT, IIT Kharagpur, India. Reporter : S.Y.Chen. Abstract.

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Resource Selection in Grids Using Contract Net

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  1. Resource Selection in Grids Using Contract Net Kunal Goswami, Arobinda Gupta Cisco Systems, Bangalore, India Dept. of Computer Science & Engineering and School of IT, IIT Kharagpur, India Reporter:S.Y.Chen

  2. Abstract • Different market mechanisms have been used to match resources with users in grids. In this paper, we propose two simple contract-net based resource selection policies in grids with heterogeneous resources. A detailed experimental evaluation of the policies shows that they perform better than other commonly used policies for many scenarios. S.Y. Chen

  3. Outline • Introduction • System Model • Resource Selection Policies • Experimental Results. S.Y. Chen

  4. Introduction • Choosing the right resource for a user job is an important problem in Grid. • We propose two simple contract net based resource selection policies. S.Y. Chen

  5. Introduction (cont.) • The policies increase the number of jobs finishing within budget and deadline while reducing the averageturnaround time per job or the average budget spent per job at the same time. S.Y. Chen

  6. Introduction (cont.) • Previous works on using contract net for resource selection in grids with heterogeneous resources either only attempted to increase the number of jobs finishing within deadlines, or attempted to reduce the cost of execution of a job. S.Y. Chen

  7. System Model S.Y. Chen

  8. System Model (cont.) S.Y. Chen

  9. System Model (cont.) S.Y. Chen

  10. System Model (cont.) S.Y. Chen

  11. Resource Selection Policies • Some policies that have been used in prior works in resource selection in grids are random, time optimized and cost-optimized. • In a random policy, a user randomly chooses one resource that can complete the job within the deadline and budget allocated for the job. • It may increase both the execution time and the cost of execution of a job. S.Y. Chen

  12. Resource Selection Policies (cont.) • In a time-optimized or cost-optimized policy, the fastest or the cheapest resource is selected respectively. • A pure time-optimized strategy or a pure cost-optimized strategy can cause higher speed or lower cost resources to become overloaded respectively, thereby reducing the success rate. S.Y. Chen

  13. Resource Selection Policies (cont.) • K-Time-Optimized • K-Cost-Optimized S.Y. Chen

  14. Experimental Results • Users:10 • Resources:10 • Jobs:100 • The resources have different speeds and cost per unit time of usage as shown below. S.Y. Chen

  15. Experimental Results (cont.) • Evaluation of the K-Time-Optimized Policy • Success rate for different job lengths S.Y. Chen

  16. Experimental Results (cont.) • Success rate for the three policies • K = 4 • Job length is 150,000 • Arrival rate 0.001 ~ 0.03 S.Y. Chen

  17. Experimental Results (cont.) • Effect of Arrival Rate • K = 4 • Job length is 150,000 • Arrival rate 0.002 ~ 0.06 S.Y. Chen

  18. Experimental Results (cont.) • Effect of job length • K = 4 • Arrival rate = 0.01 S.Y. Chen

  19. Experimental Results (cont.) • Evaluation of the K-Cost-Optimized Policy S.Y. Chen

  20. Experimental Results (cont.) • The success rate for the three policies. S.Y. Chen

  21. Experimental Results (cont.) • The average budget spent for the three policies. S.Y. Chen

  22. Experimental Results (cont.) • Effect of Arrival Rate • K = 4 • Job length is 100,000 • Arrival rate 0.002 ~ 0.06 S.Y. Chen

  23. Experimental Results (cont.) • Effect of Job Length • K = 4 • Arrival rate is 0.01 S.Y. Chen

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