A multiobjective metaheuristic-based container consolidation model for cloud application performance improvement

A multiobjective metaheuristic-based container consolidation model for cloud application performance improvement | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A multiobjective metaheuristic-based container consolidation model for cloud application performance improvement Vincent Bracke, José Santos, Tim Wauters, Filip De Turck, Bruno Volckaert This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3755486/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Jun, 2024 Read the published version in Journal of Network and Systems Management → Version 1 posted 7 You are reading this latest preprint version Abstract This work describes an approach to enhance container orchestration platforms with an autonomous and dynamic rescheduling system that aims at improving application service time by co-locating highly interdependent containers for network delay reduction. Unreasonable container consolidation may however lead to host CPU saturation, in turn impairing the service time. The multiobjective approach proposed in this work aims to improve application service time by minimizing both inter-server network traffic and CPU throttling on overloaded servers. To this extent, the Simulated Annealing combinatorial optimization heuristic is used and compared on its relative performance towards the optimal solution obtained by Mathematical Programming. Additionally, the impact of the proposed system is validated on a Kubernetes cluster hosting three concurrent applications, and this under varying load scenarios. The proposed rescheduling system systematically i) improves the application service time (up to 27.2% from our experiments) and ii) surpasses the improvement reached by the Kubernetes descheduler. Cloud Computing Services Kubernetes Container Scheduling Mathematical Optimization Autonomic and Cognitive Management Performance Management Full Text Additional Declarations Competing interest reported. Filip De Turck, a listed author, is member of the JNSM editorial advisory board. The authors declare that they have no other competing interests. Cite Share Download PDF Status: Published Journal Publication published 18 Jun, 2024 Read the published version in Journal of Network and Systems Management → Version 1 posted Editorial decision: Revision requested 10 May, 2024 Reviews received at journal 10 May, 2024 Reviewers agreed at journal 10 May, 2024 Reviewers invited by journal 10 May, 2024 Editor assigned by journal 04 Mar, 2024 Submission checks completed at journal 15 Dec, 2023 First submitted to journal 14 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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