Multilevel Task Offloading and Resource Optimization of Edge Computing Networks Considering UAV Relay and Green Energy

Applied Sciences

Nan Xiao¹  Dongsheng Han¹  Zhixiong Chen¹ 

[1] Department of Electronics and Communication Engineering, North China Electric Power University, Baoding 071003, China;

关键词: Unmanned aerial vehicle (UAV);    Mobile Edge Computing (MEC) Network;    green energy resources;    MDP algorithm;   

DOI  :  10.3390/app10072592

来源: DOAJ

【 摘 要 】

Unmanned aerial vehicle (UAV)-assisted relay mobile edge computing (MEC) network is a prominent concept, where network deployment is flexible and network coverage is wide. In scenarios such as emergency communications and low-cost coverage, optimization of offloading methods and resource utilization are important ways to improve system effectiveness due to limited terminal and UAV energy and hardware equipment. A multilevel edge computing network resource optimization model on the basis of UAV fusion that provides relay forwarding and offload services is established by considering the initial energy state of the UAV, the green energy charging function, and the reliability of computing offload. With normalized system utility function maximization as the goal, a Markov decision process algorithm meets the needs of the practical application scene and provides a flexible and effective unloading mode. This algorithm is adopted to solve the optimal offloading mode and the optimal resource utilization scheme. Simulations verify the effectiveness and reliability of the proposed multilevel offloading model. The proposed model can optimize system resource allocation and effectively improve the utility function and user experience of computing offloading systems.

【 授权许可】

Unknown