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Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks
- Source :
- EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-17 (2021)
- Publication Year :
- 2020
- Publisher :
- Research Square Platform LLC, 2020.
-
Abstract
- Recently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV are rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($$\mathbf {P}_{\mathbf {T}}$$ P T ), resource allocation at UAV ($$\mathbf {P}_{\mathbf {R}}$$ P R ) and offloading decisions at IoT devices ($$\mathbf {P}_{\mathbf {O}}$$ P O ) and then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.
- Subjects :
- Computer Networks and Communications
Computer science
Distributed computing
UAV
Trajectory
lcsh:TK7800-8360
02 engineering and technology
lcsh:Telecommunication
lcsh:TK5101-6720
0202 electrical engineering, electronic engineering, information engineering
Quality of experience
Block (data storage)
Mobile edge computing
Node (networking)
MEC
lcsh:Electronics
020206 networking & telecommunications
Trajectory optimization
Energy consumption
Computer Science Applications
Collaborative offloading
Task (computing)
Signal Processing
Resource allocation
Time-sensitivity
020201 artificial intelligence & image processing
QoE
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-17 (2021)
- Accession number :
- edsair.doi.dedup.....84318fc4a7f0ad866f8e76c094e37442