Joint Task Offloading, Resource Allocation, and Trajectory Design for Multi-UAV Cooperative Edge Computing With Task Priority
Qilu University of Technology · Shandong University · +4 more institutions
Abstract
Mobile edge computing (MEC) has emerged as a solution to address the demands of computation-intensive network services by providing computational capabilities at the network edge, thus reducing service delays. Due to the flexible deployment, wide coverage and reliable wireless communication, unmanned aerial vehicles (UAVs) have been employed to assist MEC. This paper investigates the task offloading problem in a UAV-assisted MEC system with collaboration of multiple UAVs, highlighting task priorities and binary offloading mode. We defined the system gain based on energy consumption and task delay. The joint optimization of UAVs' trajectory design, binary offloading decision, computation resources allocation,…
Citation impact
- FWCI
- 178.44
- Percentile
- 100%
- References
- 43
Authors
5- HHHao HaoCorresponding
Qilu University of Technology, Shandong University, Nanjing University of Posts and Telecommunications, Shandong Academy of Sciences
- CXChangqiao Xu
Beijing University of Posts and Telecommunications
- WZWei Zhang
Qilu University of Technology, Shandong University, Nanjing University of Posts and Telecommunications, Shandong Academy of Sciences
- SYShujie Yang
Beijing University of Posts and Telecommunications
- GMGabriel‐Miro Muntean
Dublin City University
Topics & keywords
- Computer science
- Mobile edge computing
- Computation offloading
- Reinforcement learning
- Distributed computing
- Edge computing
- Resource allocation
- Resource management (computing)
- Affordable and clean energy