Minimizing Maximum Latency of Task Offloading for Multi-UAV-Assisted Maritime Search and Rescue

被引:4
作者
Qi, Shuang [1 ]
Lin, Bin [1 ]
Deng, Yiqin [2 ,3 ]
Chen, Xianhao [4 ,5 ]
Fang, Yuguang [6 ]
机构
[1] Dalian Maritime Univ, Informat Sci & Technol Coll, Dalian 116026, Peoples R China
[2] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
[3] Shandong Key Lab Wireless Commun Technol, Jinan 250061, Peoples R China
[4] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Peoples R China
[5] Univ HongKong, HKU Musketeers Fdn Inst Data Sci, Hong Kong, Peoples R China
[6] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous aerial vehicles; Task analysis; Streaming media; Delays; Disasters; Real-time systems; Optimization; UAV; computing offloading; disaster area surveillance; edge computing; OPTIMIZATION; SCHEME;
D O I
10.1109/TVT.2024.3384570
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Unmanned Aerial Vehicles (UAVs) play a crucial role in Maritime Search and Rescue (MSAR), contributing to the improvement of rescue efficiency and reduction of casualties. Typically, UAVs equipped with cameras collect data from disaster areas and transmit it to the shore-based rescue command centers. By deploying Mobile Edge Computing (MEC) servers, UAVs can pre-process video footage to reduce data transmission volume, thus reducing transmission delays. However, the limited computational capacity and energy of UAVs pose significant challenges to the efficiency of UAV-assisted MSAR systems. To address these problems, in this paper, we investigate a multi-UAV assisted MSAR system consisting of multiple Surveillance UAVs (S-UAVs) and a Relay UAV (R-UAV). Then, we formulate a joint optimization problem to minimize the maximum total latency among all S-UAVs via jointly making the computing offloading decisions, R-UAV deployment, and the association between a S-UAV and rescue targets while ensuring that all targets are monitored by S-UAVs. Since the formulated optimization problem is typically hard to solve due to its non-convexity, we propose an effective iterative algorithm by breaking it into three sub-problems. Numerical simulation results show the effectiveness of the proposed algorithm with various performance parameters.
引用
收藏
页码:13625 / 13638
页数:14
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