journal article·2020Open access

Resource Allocation in Edge-Computing Based Wireless Networks Based on Differential Game and Feedback Control

Ruijie Lin, Haitao Xu, Meng Li, Zhen Zhang

Computers, Materials & Continua· Volume 64· Issue 2

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.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: IoT and Edge/Fog Computing · Age of Information Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References

Reference metadata was not supplied for this record.