A Workflow Scheduling in Cloud Environment Using a Combination of Moth-Flame and Salp Swarm Algorithms

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL A Workflow Scheduling in Cloud Environment Using a Combination of Moth-Flame and Salp Swarm Algorithms 26 Pages Posted: 12 Sep 2022 See all articles by Li QiaoLi QiaoLvliang Universitysaeed naderiaffiliation not provided to SSRNMahmood Ahmadiaffiliation not provided to SSRNSeyedali MirjaliliGriffith University Abstract Cloud computing is a computing model based on computer networks such as the Internet that provides a new model for the supply, consumption, and delivery of computing services using the network. With the increase in user requests and their diversity, and with the increase in the demand of scientific workflows, the need for an optimal workflow scheduling method to increase the quality of cloud server services to different users increases. In this paper, the workflow scheduling in the cloud environment is examined and different servers that have different numbers of heterogeneous Virtual Machines (VMs) are examined. Therefore, a multi-objective workflow scheduling method using a combination of Moth-Flame Optimization (MFO) and Salp Swarm Algorithm (SSA), MFSSA with different objectives (makespan time, throughput , resource utilization, and reliability) is proposed. The main goal of the MFSSA algorithm is to find the optimal servers and VMs based on the minimization of the objective function, as a result of which the best VM for each task of workflow is obtained. In addition, a technique is proposed to select the best server and the best VM to execute the workflow tasks. Experimental results demonstrate that MFSSA is better than MFO, Particle Swarm Optimization algorithms (PSO), Harris Hawks Optimization (HHO), Firefly Algorithm (FA), and SSA in terms of various Quality of Service (QoS) metrics, including objective function value, resources utilization (%), throughput, reliability, and makespan time. Keywords: workflow scheduling, cloud computing, optimization, meta-heuristic, Moth-Flame Optimization, and Salp Swarm Algorithm. Suggested Citation: Suggested Citation Qiao, Li and naderi, saeed and Ahmadi, Mahmood and Mirjalili, Seyedali, A Workflow Scheduling in Cloud Environment Using a Combination of Moth-Flame and Salp Swarm Algorithms. Available at SSRN: https://ssrn.com/abstract=4216421 Li Qiao (Contact Author) Lvliang University ( email ) Saeed Naderi affiliation not provided to SSRN ( email ) No Address Available Mahmood Ahmadi affiliation not provided to SSRN ( email ) No Address Available Seyedali Mirjalili Griffith University ( email ) 170 Kessels RoadNathan, Queensland QLD 4111Australia Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? Place Job Opening Paper statistics Downloads 0 Abstract Views 2 PlumX Metrics Related eJournals Computation Theory eJournal Follow Computation Theory eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 175 PAPERS 3,099 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo-4dc in 0.195 seconds