A Stochastic Games based Resource Allocation Method for Cloud based Safe Computing Platform

被引:0
|
作者
Zhang, Zhilin [1 ]
Lv, Fei [1 ]
Ying, Zhipeng [2 ]
Wang, Xi [1 ]
Zhao, Hongli [1 ]
Tang, Tao [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[2] China Acad Railway Sci, Signals & Commun Res Inst, Beijing 100081, Peoples R China
[3] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
来源
2023 IEEE 26TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, ITSC | 2023年
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Cloud computing; Safe computing platform; Stochastic games; Resources allocation;
D O I
10.1109/ITSC57777.2023.10422237
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Safe computing platform is a safe architecture for the wayside equipment of CBTC, which keeps train operation control safely and efficiently in urban rail transit system. With the expansion of the subway line and the increase of passenger flow, the cloud computing technology is introduced into transit system to cope with the increase of maintenance cost and accident risk probability caused by the increase of physical equipments of CBTC. However, the architecture of safe computing platform must be considered when transplant the physical wayside equipment to cloud servers, which is hard to allocate the resources for the wayside equipment softwares to realize a good load-balance value while meeting the safety requirements defined by the safe computing platform. As one of the standard analytical tools, game theory has been applied in various fields to analyze resource allocation and decision-making problems. And stochastic games is good at modeling multi-agent decision-making problems, which is suitable for the problem we face. In this paper, a stochastic games is utilized to formulate the resource allocation of the cloud servers among the safe computing platform softwares and a SARSA based resources allocation algorithm with safety requirements is proposed to solve it. We compare SRAS with other similar algorithms in some simulation scenarios. The simulation results show that the SRAS method can get a better convergence performance and load-balance value of the cloud servers.
引用
收藏
页码:2428 / 2433
页数:6
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