Open AccessTeaching-Learning Based Task Scheduling Optimization in Cloud Computing Environments
Author(s) -
Ramakrishna Goddu,
Kiran Kumar Reddi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b2672.078219
Subject(s) - computer science , cloud computing , scheduling (production processes) , distributed computing , dynamic priority scheduling , two level scheduling , task (project management) , fair share scheduling , job shop scheduling , mathematical optimization , operating system , schedule , mathematics , management , economics
Generating optimal task scheduling plans in cloud environments is a tedious task as it is a np-hard problem. The optimal resource allocation in cloud environments involves more search space and time consuming. Therefore, recent researchers are focused on implementation of artificial intelligence to solve task scheduling problem. In this paper, a new and efficient evolutionary algorithm named teaching-learning based algorithm has been implemented first time to solve the task scheduling problem in cloud environments. The current research work considers the task scheduling problem as a multi-objective optimization problem. The proposed algorithm finds the best solution by minimizing the execution time and response time while maximizing the throughput of all resources to complete the assigned tasks.