Research Article
A Two-Level Adaptive Resource Allocation Algorithm for Quality of Service Guarantee in Home WiFi Networks
@INPROCEEDINGS{10.1007/978-3-031-31275-5_19, author={ZhanYu Zhang and Bo Li and Zhongjiang Yan and Mao Yang}, title={A Two-Level Adaptive Resource Allocation Algorithm for Quality of Service Guarantee in Home WiFi Networks}, proceedings={Smart Grid and Internet of Things. 6th EAI International Conference, SGIoT 2022, TaiChung, Taiwan, November 19-20, 2022, Proceedings}, proceedings_a={SGIOT}, year={2023}, month={5}, keywords={Home WiFi Network TRAQ Call Loss Rate Services Starved}, doi={10.1007/978-3-031-31275-5_19} }- ZhanYu Zhang
Bo Li
Zhongjiang Yan
Mao Yang
Year: 2023
A Two-Level Adaptive Resource Allocation Algorithm for Quality of Service Guarantee in Home WiFi Networks
SGIOT
Springer
DOI: 10.1007/978-3-031-31275-5_19
Abstract
Aiming at the problem that the service quality of audio and video, large file transmission and other services is difficult to guarantee in the home Wireless Fidelity (WiFi) network, this paper proposes a two-level adaptive resource allocation algorithm for quality of service guarantee (TRAQ), which can effectively avoid the starvation of large file transmission, to improve the success rate of audio and video service establishment and the fairness of multiple large file transmissions. Firstly, the quality-of-service guarantee problem of audio and video, large file transmission is modeled as the resource allocation problem in the scheduling period, with the goal of minimizing the Gini coefficient of multiple large file transmission rates and the constraint of ensuring the average transmission rate of all large files and the call loss rate of audio and video. Then, the arrival and service process of audio and video services is modeled as a M/M/m/m queuing model, and the first-level resource allocation ratio between the audio and video services and the large files services is obtained. Secondly, the second-level resource allocation ratio minimizing the Gini coefficient of large file transmission services is derived. Finally, the simulation results show that the proposed TRAQ not only balances the service requirements between the two types of services, but also achieves a certain transmission fairness within the large file transmission services.
