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中国工业与应用数学学会会刊
主管:中华人民共和国教育部
主办:西安交通大学
ISSN 1005-3085  CN 61-1269/O1

工程数学学报 ›› 2017, Vol. 34 ›› Issue (5): 490-506.doi: 10.3969/j.issn.1005-3085.2017.05.005

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优先权下大型交互对抗服务网络的稳定性研究

李泉林,   张   瑜   

  1. 燕山大学经济管理学院,秦皇岛  066004
  • 收稿日期:2015-10-12 接受日期:2017-02-20 出版日期:2017-10-15 发布日期:2017-12-15
  • 基金资助:
    国家自然科学基金(71271187; 71471160; 71671158);河北省自然科学基金(G2017203277);河北省高等学校创新团队领军人才培育计划(LJRC027).

Research on Stability of Large-scale Adversarial Service Networks under Priority

LI Quan-lin,   ZHANG Yu   

  1. School of Economics and Management, Yanshan University, Qinhuangdao 066004
  • Received:2015-10-12 Accepted:2017-02-20 Online:2017-10-15 Published:2017-12-15
  • Supported by:
    The National Natural Science Foundation of China (71271187; 71471160; 71671158); the Natural Science Foundation of Hebei Province (G2017203277); the Innovative Team and Leader Talent Cultivation Plan of Higher Education in Hebei Province (LJRC027). 

摘要: 近年来,物联网、大数据与云计算为各种大型服务系统及其资源管理与任务调度提供了新的信息技术,也导致了这些服务系统中出现了大范围、松耦合、跨组织与异构性等多种关键特征.为了研究这些大型服务系统,交互对抗网络(Adversarial Networks)以其简便的确定性假设与直观的稳定性评估等优点而成为国际上一个热点且重要的研究方向.本文首先分析了一个具有优先权的环形交互对抗服务网络,并通过数学建模提出了一种确定性上界估计方法,由此讨论了这种网络的系统稳定性问题.然后,研究了系统性能指标并且给出了任意一个顾客在网络中运行时间的一个上界.最后,通过数值算例研究了网络中两类顾客总数的上界以及它们在网络中运行时间的上界是如何依赖网络中的一些关键参数.

关键词: 交互对抗服务网络, 优先权, 调度机制, 稳定性

Abstract: Recently, internet of things, big data and cloud computing provide new information technologies for a variety of large-scale service systems and for their resource management and task scheduling, and they also lead to many crucial characteristics, such as, large scale, loose coupling, cross organizations, heterogeneity and so on. To study the large-scale service systems, the adversarial networks becomes a hot and interesting research direction through a simply deterministic hypothesis and an upper bound estimation for system stability. In this paper, we firstly analyze a directed ring of service adversarial network with priority, and develop an upper bound estimation method by means of a mathematical modeling and analysis, hence also propose a new discussion of system stability. Then, we study the performance measures of this network, and also provide an upper bound of the running time that each customer is served in the adversarial network. Finally, we give some numerical examples to demonstrate how the upper bounds of the total number of customers and of the running time of each customer depend on some key parameters of this adversarial network.

Key words: adversarial service network, priority, scheduling mechanism, stability

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