AN EFFECTIVE METHOD FOR QOS -CONSTRAINED WORK FLOW SCHEDULING OF CLOUD SERVICES

Authors

  • Sabarinathan N

DOI:

https://doi.org/10.20894/IJMSR.117.003.001.002

Keywords:

Cloud computing; SaaS Clouds; Grid computing; Workflow scheduling; QoS-based scheduling.

Abstract

Cloud computing is the most recent promising trending that provides hardware infrastructures and software applications as a service. Users can use these services through Service Level Agreement (SLA) which defines user's essential Quality of Service (QoS) parameters on pay-per-use basis. In cloud computing the workflow scheduling is a difficult problem to be solved. Normally the scheduling methods are tried to diminish the execution time of the workflows. There are several existing approaches to solve the difficulty of multi-objective scheduling in cloud but, there exists the problem of computational complexity and the budget constraints. To overcome this problem, in existing the SaaS Cloud Partial Critical Paths (SC-PCP) algorithm was enhanced, which is an extension of the preceding one for the SaaS Clouds. The idea of the SC-PCP algorithm is to form a schedule that decreases the total execution cost of a workflow, while satisfying a user defined deadline for the total execution time. In this work the main problem is that the time and cost are the only considered as parameters for the deadline. To overcome this problem, in proposed work, there are three proposals are followed. The first proposal is; QoS needed by the customers for selecting a Cloud service provider is based on: Accountability, Agility, Assurance of Service, Security and Privacy, and Usability where the drawback of existing method is solved. To solve this problem as a second proposal work, a (Price- and-Time-Slot-Negotiation) PTN mechanism devised that enables both providers and customers to do the following: 1) specify their preferences for price and time slot and 2) search for mutually acceptable prices and time slots. Finally, quantifying the performance of scheduling and allocation policy on a Cloud infrastructure (hardware, software, services) for different application and service models below unreliable load energy performance (power consumption, heat dissipation), and system dimension is an extremely challenging problem to tackle. To overcome this problem, the SC-PCP algorithm is expanded to support other IaaS Cloud computing model. This final proposal work can be implemented with the use of cloud sim.

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Author Biography

Sabarinathan N

Computer science Engineering, Sri Jayaram Engineering College, Anan University, Chennai, Tamilnadu, India.

References

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Published

2011-12-20

Issue

Vol. 3 No. 1 (2011)

Section

Articles

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