APOLLO: A Proximity-Oriented Low-Level Orchestration Algorithm for Performance Optimization in Mist Computing

APOLLO: A Proximity-Oriented Low-Level Orchestration Algorithm for Performance Optimization in Mist Computing | 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 APOLLO: A Proximity-Oriented Low-Level Orchestration Algorithm for Performance Optimization in Mist Computing Messaoud Babaghayou, Noureddine Chaib, Leandros Maglaras, Yagmur Yigit, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4110099/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The fusion of satellite technologies with the Internet of Things (IoT) has propelled the evolution of mobile computing, ushering in novel communication paradigms and data management strategies. Within this landscape, the efficient management of computationally intensive tasks in satellite-enabled mist computing environments emerges as a critical challenge. These tasks, spanning from optimizing satellite communication to facilitating blockchain-based IoT processes, necessitate substantial computational resources and timely execution. To address this challenge, we introduce APOLLO, a novel low-layer orchestration algorithm explicitly tailored for satellite mist computing environments. APOLLO leverages proximity-driven decision-making and load balancing to optimize task deployment and performance. We assess APOLLO's efficacy across various configurations of mist layer devices while employing a round-robin principle for equitable task distribution among the close low-layer satellites. Our findings underscore APOLLO's promising outcomes in terms of reduced energy consumption, minimized end-to-end delay, and optimized network resource utilization, particularly in targeted scenarios. However, the evaluation also reveals avenues for refinement, notably in CPU utilization and slightly low tasks success rates. Our work contributes substantial insights into advancing task orchestration in satellite-enabled mist computing with more focus on energy and end-to-end sensitive applications, paving the way for more efficient, reliable, and sustainable satellite communication systems. Satellite Edge Computing Task Management Task Orchestration Low-Layer Satellites communication Energy-efficient Offloading End-to-End Delay Reduction. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Apr, 2024 Reviews received at journal 08 Apr, 2024 Reviewers agreed at journal 30 Mar, 2024 Reviews received at journal 29 Mar, 2024 Reviewers agreed at journal 29 Mar, 2024 Reviews received at journal 28 Mar, 2024 Reviewers agreed at journal 28 Mar, 2024 Reviewers invited by journal 28 Mar, 2024 Editor assigned by journal 28 Mar, 2024 Submission checks completed at journal 25 Mar, 2024 First submitted to journal 15 Mar, 2024 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4110099","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283743848,"identity":"b430b05d-c349-4df9-9255-f5b6bc318065","order_by":0,"name":"Messaoud Babaghayou","email":"","orcid":"","institution":"University of Laghouat","correspondingAuthor":false,"prefix":"","firstName":"Messaoud","middleName":"","lastName":"Babaghayou","suffix":""},{"id":283743850,"identity":"a6ad90a6-470c-4c5a-939a-e884a8c8f945","order_by":1,"name":"Noureddine Chaib","email":"","orcid":"","institution":"University of 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