Abstract

Cloud infrastructure is a pay-per-use, easily scalable, and accessible model. Based on the requirements of the workflow application, provisioning of resources can be dynamically done as the cloud is elastic in nature. The objective of this work is to execute scientific workflows within user deadlines having minimal expense and the total execution time. Appropriate provisioning and scheduling of all the tasks can effectively decrease the execution time in scientific workflows. This work suggests fuzzy scheduling for improvising the efficacy of energy as well as security. A major role in cloud computing is made by fuzzy logic theory. This work describes an approach for addressing the energy as well as security constraints in the cloud using the fuzzy controller. By referring to the fuzzy inference knowledge base, the duration, energy consumption and trust metrics can be inferred using fuzzy logic, based on the user task types. The system realizes the dynamic scheduling of the resources as per the specific needs. This achieves the purpose of improving the execution ratio and the utilization of resources. It has been demonstrated through the outcomes that the suggested scheduling algorithm can be efficiently deployed on the cloud.

Authors

P. Tharani, K. Manimala, A.M. Kalpana
Government College of Engineering, Salem, India

Keywords

Fuzzy Scheduling, Scientific Workflow, Partial Critical Path (PCP), Energy Factor, Cloud Computing