{"title":"Joint Trajectory Planning and Task Offloading for MIMO AAV-Aided Mobile Edge Computing","authors":"Xuewen Dong;Shuangrui Zhao;Ximeng Liu;Zijie Di;Yuzhen Zhang;Yulong Shen","doi":"10.1109/TMC.2024.3510272","DOIUrl":null,"url":null,"abstract":"Edge computing is conducive to reducing service response time and improving service quality by pushing cloud functions to a network's edges. Most existing works in edge computing focus on utility maximization of task offloading on static edges with a single antenna. Besides, trajectory planning of mobile edges, e.g., autonomous aerial vehicles (AAVs) is also rarely discussed. In this paper, we are the first to jointly discuss the deadline-ware task offloading and AAV trajectory planning problem in a multi-input multi-output (MIMO) AAV-aided mobile edge computing system. Due to discrete variables and highly coupling nonconvex constraints, we equivalently convert the original problem into a more solvable form by introducing auxiliary variables. Next, a penalty dual decomposition-based algorithm is developed to achieve a global optimal solution to the problem. Besides, we proposed a profit-based fireworks algorithm in a relatively lower time to reduce the execution time for large-scale networks. Extensive evaluation results reveal that our proposed optimal algorithms could significantly outperform static offloading algorithms and other algorithms by 25% on average.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 4","pages":"3196-3210"},"PeriodicalIF":7.7000,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10772328/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Edge computing is conducive to reducing service response time and improving service quality by pushing cloud functions to a network's edges. Most existing works in edge computing focus on utility maximization of task offloading on static edges with a single antenna. Besides, trajectory planning of mobile edges, e.g., autonomous aerial vehicles (AAVs) is also rarely discussed. In this paper, we are the first to jointly discuss the deadline-ware task offloading and AAV trajectory planning problem in a multi-input multi-output (MIMO) AAV-aided mobile edge computing system. Due to discrete variables and highly coupling nonconvex constraints, we equivalently convert the original problem into a more solvable form by introducing auxiliary variables. Next, a penalty dual decomposition-based algorithm is developed to achieve a global optimal solution to the problem. Besides, we proposed a profit-based fireworks algorithm in a relatively lower time to reduce the execution time for large-scale networks. Extensive evaluation results reveal that our proposed optimal algorithms could significantly outperform static offloading algorithms and other algorithms by 25% on average.
期刊介绍:
IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.