Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud Computing Environment for Efficient Resource Scheduling for Distributed Overloading  

作　　者：Anurag Sinha Pallab Banerjee Sharmistha Roy Nitasha Rathore Narendra Pratap Singh Mueen Uddin Maha Abdelhaq Raed Alsaqour 

机构地区：[1]Department of Computer Science Engineering,ICFAI Tech School,ICFAI University,Jharkhand,Ranchi,834004,India [2]Department of Computer Science Engineering,Amity University,Jharkhand,Ranchi,835303,India [3]Department of Computing and Information Technology,Usha Martin University,Ranchi,835103,India [4]Department of Information Technology,Bharti Vidyapeeth’s College of Engineering,Paschim Vihar,New Delhi,India [5]Department of CSE,Delhi University,New Delhi,India [6]College of Computing and Information Technology,University of Doha for Science and Technology,Doha,24449,Qatar [7]Department of Information Technology,College of Computer and Information Sciences,Princess Nourah Bint Abdurrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [8]Department of Information Technology,College of Computing and Informatics,Saudi Electronic University,93499,Riyadh,Saudi Arabia

出　　处：《Journal of Systems Science and Systems Engineering》2024年第4期391-424,共34页系统科学与系统工程学报（英文版）

基　　金：funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project(No.PNURSP2023R97);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.

摘　　要：This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task allocation.Utilizing Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task completion.It advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue lengths.The Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative analysis.The research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

关 键 词：First come first served(FCFS)scheduling round robin task scheduling queuing model Johnson scheduling algorithm 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]