Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

作     者：Anwar R Shaheen Sundar Santhosh Kumar 

作者机构：Department of Computer ScienceAlagappa UniversityKaraikudiIndia 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第35卷第3期

页      面：2963-2978页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Task scheduling virtual machines(VM) particle swarm optimization(PSO) bandwidth aware divisible task scheduling(BATS) multi-layered regression 

摘      要：Cloud computing plays a significant role in Information Technology(IT)industry to deliver scalable resources as a *** of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task *** main advantage of this scheduling is to max-imize the performance and minimize the time *** researchers examined numerous scheduling methods to achieve Quality of Service(QoS)and to reduce execution ***,it had disadvantages in terms of low throughput and high response ***,this study aimed to schedule the task efficiently and to eliminate the faults in scheduling the tasks to the Virtual Machines(VMs).For this purpose,the research proposed novel Particle Swarm Optimization-Bandwidth Aware divisible Task(PSO-BATS)scheduling with Multi-Layered Regression Host Employment(MLRHE)to sort out the issues of task scheduling and ease the scheduling operation by load *** proposed efficient sche-duling provides benefits to both cloud users and *** performance evalua-tion is undertaken with respect to cost,Performance Improvement Rate(PIR)and makespan which revealed the efficiency of the proposed ***,comparative analysis is undertaken which confirmed the performance of the intro-duced system than conventional system for scheduling tasks with highflexibility.