Work place: Department of CSE, GITAM University, Hyderabad, India
E-mail: phanikumar.s@gmail.com
Website:
Research Interests: Computer systems and computational processes, Computer Vision, Systems Architecture, Information Systems
Biography
Dr.S.Phani Kumar Received his B.E from REC,Bhalki, M.Tech in Software Engineering and Ph.D in CSE from Bharath University, Chennai,India. He is presently working as Professor and HOD of CSE Department at GITAM University,Hyderabad. His research interests include cloud computing, Safety critical systems, software safety, Fault tolerant systems, Computer vision and Machine intelligence.
By G. Narendrababu Reddy S. Phani Kumar
DOI: https://doi.org/10.5815/ijisa.2019.01.08, Pub. Date: 8 Jan. 2019
Cloud computing is the development of distributed computing, parallel computing, and grid computing, or defined as a commercial implementation of such computer science concepts. One of the main issues in a cloud computing environment is Task scheduling (TS). In Cloud task scheduling, many Non deterministic Polynomial time-hard optimization problem, and many meta-heuristic (MH) algorithms have been proposed to solve it. A task scheduler should adapt its scheduling strategy to changing environment and variable tasks. This paper amends a cloud task scheduling policy based on Modified Ant Colony Optimization (MACO) algorithm. The main contribution of recommended method is to minimize makespan and to perform Multi Objective Task Scheduling (MOTS) process by assigning pheromone amount relative to corresponding virtual machine efficiency. MACO algorithm improves the performance of task scheduling by reducing makespan and degree of imbalance comparatively lower than a basic ACO algorithm by its multi-objective and deliberate nature.
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