Research Area:  Cloud Computing

Abstract:

Cloud computing is the development of distributed computing, parallel computing, and grid computing, or defined as commercial implementation of such computer science concepts. One among the day-to-day challenges in cloud computing environment is task scheduling (TS). TS is the process of allocating cloudlets to virtual machines (VM) in a cloud architecture with a concern of effective load balance and efficient utilization of resources. With the aim of facing challenges in cloud task scheduling, many non-deterministic polynomial time-hard optimization problem-solving techniques 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. Main contribution of recommended scheme is to minimize makespan and to perform multi-objective task scheduling (MOTS) process. MACO algorithm will improve performance of task scheduling by reducing makespan and degree of imbalance comparatively lower than basic ACO algorithm.

Keywords:  

Author(s) Name:  G. Narendrababu Reddy,S. Phani Kumar

Publisher name:  Springer

DOI:  10.1007/978-981-13-1921-1_36

Volume Information:  pp 357-365

Paper Link:   https://link.springer.com/chapter/10.1007/978-981-13-1921-1_36