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Deadline Constrained Workflow Scheduling Optimization by Initial Seeding with ANT Colony Optimization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 155 - Number 14 |
| Year of Publication: 2016 |
| Authors: Neel Sinha, Vishesh Srivastav, Waquar Ahmad |
10.5120/ijca2016912409
|
Neel Sinha, Vishesh Srivastav, Waquar Ahmad . Deadline Constrained Workflow Scheduling Optimization by Initial Seeding with ANT Colony Optimization. International Journal of Computer Applications. 155, 14 ( Dec 2016), 24-29. DOI=10.5120/ijca2016912409
Abstract
Cloud computing is a new model of service provisioning in distributed systems. It encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in workflow scheduling in cloud environment is its quality of service, which minimizes the cost of computation of workflows. In this paper, we use the Predicted Earliest finish time (PEFT) for initial seeding to Ant Colony optimization technique (ACO). As we know ACO is a very powerful technique appropriate for optimization.. The increasing complexity of the workflow applications is forcing researchers to explore hybrid approaches to solve the workflow scheduling problem. In this paper we proposed PEFT with ACO algorithm which reduces the initialization complexity and converge ACO algorithm.
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