{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T09:38:12Z","timestamp":1776245892872,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,22]],"date-time":"2022-05-22T00:00:00Z","timestamp":1653177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62071470"],"award-info":[{"award-number":["62071470"]}]},{"name":"National Natural Science Foundation of China","award":["61971421"],"award-info":[{"award-number":["61971421"]}]},{"name":"National Natural Science Foundation of China","award":["51874300"],"award-info":[{"award-number":["51874300"]}]},{"name":"National Natural Science Foundation of China","award":["U1510115"],"award-info":[{"award-number":["U1510115"]}]},{"name":"National Natural Science Foundation of China","award":["KC20167"],"award-info":[{"award-number":["KC20167"]}]},{"name":"National Natural Science Foundation of China","award":["20190902"],"award-info":[{"award-number":["20190902"]}]},{"name":"National Natural Science Foundation of China","award":["20190913"],"award-info":[{"award-number":["20190913"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>When an unmanned aerial vehicle (UAV) performs tasks such as power patrol inspection, water quality detection, field scientific observation, etc., due to the limitations of the computing capacity and battery power, it cannot complete the tasks efficiently. Therefore, an effective method is to deploy edge servers near the UAV. The UAV can offload some of the computationally intensive and real-time tasks to edge servers. In this paper, a mobile edge computing offloading strategy based on reinforcement learning is proposed. Firstly, the Stackelberg game model is introduced to model the UAV and edge nodes in the network, and the utility function is used to calculate the maximization of offloading revenue. Secondly, as the problem is a mixed-integer non-linear programming (MINLP) problem, we introduce the multi-agent deep deterministic policy gradient (MADDPG) to solve it. Finally, the effects of the number of UAVs and the summation of computing resources on the total revenue of the UAVs were simulated through simulation experiments. The experimental results show that compared with other algorithms, the algorithm proposed in this paper can more effectively improve the total benefit of UAVs.<\/jats:p>","DOI":"10.3390\/e24050736","type":"journal-article","created":{"date-parts":[[2022,5,22]],"date-time":"2022-05-22T07:13:57Z","timestamp":1653203637000},"page":"736","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Task Offloading Strategy Based on Mobile Edge Computing in UAV Network"],"prefix":"10.3390","volume":"24","author":[{"given":"Wei","family":"Qi","sequence":"first","affiliation":[{"name":"Department of Information Technology, Jiangsu Union Technical Institute, Xuzhou 221000, China"}]},{"given":"Hao","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Computer Sciences and Technology, China University of Mining and Technology, Xuzhou 221000, China"}]},{"given":"Lichen","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Sciences, Xi\u2019an Jiaotong-Liverpool University, Suzhou 215123, China"}]},{"given":"Shuo","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer Sciences and Technology, China University of Mining and Technology, Xuzhou 221000, China"}]},{"given":"Haifeng","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Computer Sciences and Technology, China University of Mining and Technology, Xuzhou 221000, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5051","DOI":"10.1109\/JIOT.2021.3108902","article-title":"Toward Response Time Minimization Considering Energy Consumption in Caching-Assisted Vehicular Edge Computing","volume":"9","author":"Tang","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9364","DOI":"10.1109\/TVT.2020.2970763","article-title":"Mobile Vehicles as Fog Nodes for Latency Optimization in Smart Cities","volume":"69","author":"Tang","year":"2020","journal-title":"IEEE Trans. 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