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Energy Efficient Resource Allocation and Trajectory Optimization in UAV-Assisted Mobile Edge Computing System
[发布时间:2021-08-17 阅读次数: 931]
作者：Shuaibing Chen, Lei Shi, Xu Ding, Zengwei Lv, Zhehao Li
发表刊物：BigCom 2021
年份：August 2021
摘要：Mobile edge computing(MEC) has been considered as a promising technology with the ever-increasing computation demands, which offloads computation-intensive tasks to MEC servers to meet the low latency and high bandwidth requirements of the tasks. But considering the dynamic UEs, nonuniform distribution of task requests and the limitation of the dynamic of the fixed deployment of the edge severs, we investigate a Unmanned Aerial Vehicles (UAVs)-assisted edge computing system in this paper, where each UAV is equipped with server to assist local edge servers. Utilizing the mobility of UAVs provides flexible edge computing services. In this model, tasks are executed on the local edge server first. When the computing resources of the local edge server cannot meet the computational requirements of the task, the system will dispatch the UAVs. Task will be offloaded to UAV for execution. Considering that the endurance of UAVs is a tough problem under the current technical level. Our aim is to minimize the energy consumption of UAVs under the premise of satisfying the UEs demands as much as possible to achieve a higher resource utilization rate. We propose Tasks Offloading Policy Algorithm(TOPA) and Online UAVs Dispatching Base on the Shortest Distant Algorithm(ODSH). Simulation results show the effectiveness of the proposed of algorithms.
发表刊物：BigCom 2021
年份：August 2021
摘要：Mobile edge computing(MEC) has been considered as a promising technology with the ever-increasing computation demands, which offloads computation-intensive tasks to MEC servers to meet the low latency and high bandwidth requirements of the tasks. But considering the dynamic UEs, nonuniform distribution of task requests and the limitation of the dynamic of the fixed deployment of the edge severs, we investigate a Unmanned Aerial Vehicles (UAVs)-assisted edge computing system in this paper, where each UAV is equipped with server to assist local edge servers. Utilizing the mobility of UAVs provides flexible edge computing services. In this model, tasks are executed on the local edge server first. When the computing resources of the local edge server cannot meet the computational requirements of the task, the system will dispatch the UAVs. Task will be offloaded to UAV for execution. Considering that the endurance of UAVs is a tough problem under the current technical level. Our aim is to minimize the energy consumption of UAVs under the premise of satisfying the UEs demands as much as possible to achieve a higher resource utilization rate. We propose Tasks Offloading Policy Algorithm(TOPA) and Online UAVs Dispatching Base on the Shortest Distant Algorithm(ODSH). Simulation results show the effectiveness of the proposed of algorithms.
参考文献拷贝字段：Shuaibing Chen, Lei Shi, Xu Ding, Zengwei Lv, Zhehao Li. Energy Efficient Resource Allocation and Trajectory Optimization in UAV-Assisted Mobile Edge Computing System [C]. The 7th International Conference on Big Data Computing and Communications (BigCom), Deqing, China, August 13-15, 2021: 7-13
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