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Productive Task Scheduling in Cloud Computing by using Multi-goal Swarm Optimization of Particles

Author

Listed:
  • B. SivaRama Krishna
  • T. V. Rao

Abstract

Task planning for Distributed Computing (Cloud) is a testing perspective because of the clashing necessities of end user of cloud and the Service Provider of Cloud (SPC). The test at the CSP's end is to plan tasks presented by the cloud clients in an ideal way with the end goal and it needs to fulfil the Quality of Services (QOS). The necessities of client towards running expenses of the framework to a base level of another side end for better benefit. The attention is on two targets, make traverse and cost, to be streamlined meanwhile using Meta heuristic look methods for booking autonomous tasks. Another variation of ceaseless Swarm Optimization of Particle (PSO) calculation, named Integer-PSO, is aim to tackle the bi-target task planning issue in cloud which out plays the littlest position esteem (LPE) govern based PSO strategy.

Suggested Citation

  • B. SivaRama Krishna & T. V. Rao, 2016. "Productive Task Scheduling in Cloud Computing by using Multi-goal Swarm Optimization of Particles," International Journal of Scientific Research in Science, Engineering and Technology, International Journal of Scientific Research in Science, Engineering and Technology, vol. 2(3), pages 995-1001, June.
    • Handle: RePEc:ijs:ijsrse:v2:y2016:i3:id:hijsrset2184149
    Note: Article URL: https://ijsrset.com/IJSRSET2184149
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