Truthful Mechanisms for Scheduling Selfish Related Machines Using ACO
R. Raju1, J. Mohanapriya2
1R.Raju, Research Scholar, Bharathiyar University, Coimbator, India.
2J. Mohana Priya, Computer Science & Engineering, Sri Manakula Vinayagar Engineering College, Madagadipet, Puducherry, India.
Manuscript received on January 22, 2013. | Revised Manuscript received on February 14, 2013. | Manuscript published on February 28, 2013. | PP: 467-472 | Volume-2 Issue-3, February 2013. | Retrieval Number: C1167022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Task scheduling is a major challenge in parallel and distributed systems. Task scheduling techniques in distributed systems are usually based on trusting the Accuracy of the information about the status of resources. In a commercial multi- Cloud environment, individual providers are focused towards increasing their own profits and do not care about the utility of users and other providers. In such an environment, we cannot trust the information presented by the providers. To address the scheduling problem in a commercial multi-Cloud environment using reverse auctions, propose a new truthful mechanism for scheduling single tasks on the set of resources. Then adapt the proposed mechanism to dynamically schedule workflow applications. A new pricing model and truthful scheduling mechanism to find the best resource for executing a task, Ant Colony Optimization is introduced. The proposed system is used to dynamically schedule multiple tasks using multiple servers. Also task rescheduling is achieved when the task is not completed within the time. The monetary cost and execution time of the task is more concentrated in the proposed system.
Keywords: Ant colony optimization, Dynamic scheduling, Multi-Cloud environment, Task re-scheduling.