Volume 18, No. 6, 2021
Online Makes pan And Energy Optimization Mechanism With Dynamic Task Arrival And Parallel Processing In Cloud Computing Environment
Chaya T D , Dr. Mohamed Rafi
Abstract
Cloud computing has become the main source for executing scientific experiments. It is an effective technique for distributing and processing tasks on virtual machines. Scientific workflows are complex and demand efficient utilization of cloud resources. Scheduling of scientific workflows is considered as NP-complete. The problem is constrained by some parameters such as Quality of Service (QoS), dependencies between tasks and users' deadlines, etc. There exists a strong literature on scheduling scientific workflows in cloud environments. Solutions include standard schedulers, evolutionary optimization techniques, etc. In this research work we design and develop an extension of makes pan optimization where task arrival is unknown and parallel processing. Hence to achieve that we have design and developed mechanism named OMEO (Online makes pan and energy optimization) mechanism; OMEO is designed with parallel processing and dynamic arrival of task. ; In OMEO we identify the problem of makes pan and processing time and establish the relation among them. Further an algorithm is designed which can handle the unknown processing time; followed by that we design and develop a mechanism for the dynamic arrival of task i.e. where the task arrival time is unknown. Further we evaluate OMEO by considering the scientific workflow considering the metrics, TET (Task Execution Time) by comparing with the existing model. Moreover comparative analysis shows that our model achieve better results than any other algorithm.
Pages: 1409-1428
Keywords: In recent years, cloud computing has become a hot research topic, and it is widely used in telecommunications, manufacturing, education and scientific research