Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks

Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks | 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 Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks Wentao Li, Mingxiong Zhao, Yuhui Wu, Junjie Yu, Lingyan Bao, Huan Yang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-67800/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2021 Read the published version in EURASIP Journal on Wireless Communications and Networking → Version 2 posted 11 You are reading this latest preprint version Show more versions Abstract Recently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV is rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($\mathbf{P_T}$), resource allocation at UAV ($\mathbf{P_R}$) and offloading decisions at IoT devices ($\mathbf{P_O}$), then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices. Systems and Networking UAV MEC QoE collaborative offloading trajectory time-sensitivity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Cite Share Download PDF Status: Published Journal Publication published 06 Jan, 2021 Read the published version in EURASIP Journal on Wireless Communications and Networking → Version 2 posted Editorial decision: Accept 01 Nov, 2020 Review # 3 received at journal 25 Oct, 2020 Review # 1 received at journal 24 Oct, 2020 Review # 2 received at journal 24 Oct, 2020 Reviewer # 3 agreed at journal 23 Oct, 2020 Reviewers invited by journal 22 Oct, 2020 Reviewer # 1 agreed at journal 22 Oct, 2020 Reviewer # 2 agreed at journal 22 Oct, 2020 Editor assigned by journal 14 Oct, 2020 Submission checks completed at journal 13 Oct, 2020 Editor invited by journal 13 Oct, 2020 You are reading this latest preprint version Show more versions 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. 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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-67800","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":3482617,"identity":"f44b7933-fcdb-43be-964e-bd0d1a8639f6","order_by":0,"name":"Wentao Li","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wentao","middleName":"","lastName":"Li","suffix":""},{"id":3482618,"identity":"7e3982b1-3ac8-4f73-8a11-ab62915e64c2","order_by":1,"name":"Mingxiong 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However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV is rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($\\mathbf{P_T}$), resource allocation at UAV ($\\mathbf{P_R}$) and offloading decisions at IoT devices ($\\mathbf{P_O}$), then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.","manuscriptTitle":"Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2020-10-22 15:35:55","doi":"10.21203/rs.3.rs-67800/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2020-11-02T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-10-26T00:00:00+00:00","index":3,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorInvitedReview","content":"","date":"2020-10-25T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's 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