SRA-E-ABCO: Terminal Task Offloading for Cloud-Edge-End Environments | 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 SRA-E-ABCO: Terminal Task Offloading for Cloud-Edge-End Environments Shun Jiao, Haiyan Wang, Jian Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3850436/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Mar, 2024 Read the published version in Journal of Cloud Computing → Version 1 posted 9 You are reading this latest preprint version Abstract With the rapid development of Internet technology, the cloud-edge-end computing model has gradually become an essential new computing model. Under this model, terminal task offloading is crucial to task allocation and processing. Existing terminal task offloading solutions mainly focus on optimizing the offloading strategy to minimize system delay, transmission energy consumption, and computation energy cost. However, there are some problems such as the lack of a basis for judging whether to offload or not, the lack of analysis on the attributes of the terminal devices and the edge nodes, and the lack of optimization of load balancing. To address these issues, a Service Reliability Analysis and Elite-Artificial Bee Colony Offloading model (SRA-E-ABCO) is proposed for cloud-edge-end environments. Specifically, a Service Reliability Analysis (SRA) method is proposed to assist in predicting the offloading necessity of terminal tasks and analyzing the attributes of terminal devices and edge nodes. Subsequently, a set of vectors is derived based on the analysis. An Elite Artificial Bee Colony Offloading (E-ABCO) method is proposed, which optimizes offloading decisions by combining elite populations with improved fitness formulas, position update formulas, and population initialization methods. Experiments show that the proposed model has better performance in convergence, delay and energy consumption. Cloud-edge-end Terminal device Service reliability Swarm algorithm Task offloading Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Mar, 2024 Read the published version in Journal of Cloud Computing → Version 1 posted Editorial decision: Revision requested 11 Feb, 2024 Reviews received at journal 11 Feb, 2024 Reviews received at journal 22 Jan, 2024 Reviewers agreed at journal 16 Jan, 2024 Reviewers agreed at journal 15 Jan, 2024 Reviewers invited by journal 15 Jan, 2024 Editor assigned by journal 12 Jan, 2024 Submission checks completed at journal 10 Jan, 2024 First submitted to journal 10 Jan, 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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