@Article{cmc.2020.09686,
AUTHOR = {Ruijie Lin, Haitao Xu, Meng Li, Zhen Zhang},
TITLE = {Resource Allocation in Edge-Computing Based Wireless Networks Based on Differential Game and Feedback Control},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {2},
PAGES = {961--972},
URL = {http://www.techscience.com/cmc/v64n2/39339},
ISSN = {1546-2226},
ABSTRACT = {In this paper, we have proposed a differential game model to optimally solve the 
resource allocation problems in the edge-computing based wireless networks. In the 
proposed model, a wireless network with one cloud-computing center (CC) and lots of edge 
services providers (ESPs) is investigated. In order to provide users with higher services 
quality, the ESPs in the proposed wireless network should lease the computing resources 
from the CC and the CC can allocate its idle cloud computing resource to the ESPs. We 
will try to optimally allocate the edge computing resources between the ESPs and CC using 
the differential game and feedback control. Based on the proposed model, the ESPs can 
choose the amount of computing resources from the CC using feedback control, which is 
affected by the unit price of computing resources controlled by the CC. In the simulation 
part, the optimal allocated resources for users’ services are obtained based on the Nash 
equilibrium of the proposed differential game. The effectiveness and correctness of the 
proposed scheme is also verified through the numerical simulations and results.},
DOI = {10.32604/cmc.2020.09686}
}