量子云计算量子区块链与大数据深度卷积神经网络学习智能博弈归一化系统
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论文发表信息
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英文摘要
We develop a generic game platform that can be used to model various real-world
systems with multiple intelligent cloud-computing pools and parallel-queues for
resources-competing users. Inside the platform, the software structure is modeled
as Blockchain. All the users are associated with Big Data arrival streams whose
random dynamics is modeled by triply stochastic renewal reward processes (TSRRPs).
Each user may be served simultaneously by multiple pools while each pool with
parallel-servers may also serve multi-users at the same time via smart policies
in the Blockchain, e.g., a Nash equilibrium point myopically at each fixed time
to a game-theoretic scheduling problem. To illustrate the effectiveness of our
game platform, we model the performance measures of its internal data flow
dynamics (queue length and workload processes) as reflecting diffusion with
regime-switchings (RDRSs) under our scheduling policies. By RDRS models, we
can prove our myopic game-theoretic policy to be an asymptotic Pareto
minimal-dual-cost Nash equilibrium one globally over the whole time horizon to
a randomly evolving dynamic game problem. Iterative schemes for simulating our
multi-dimensional RDRS models are also developed with the support of numerical
comparisons.
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关键词
Platform and RDRS models, scheduling game, Pareto
optimal Nash equilibrium, queueing network, random dynamical system, Big Data,
Blockchain, cloud-computing or quantum-cloud-computing with multiple pools,
multi-input multi-output wireless channels, Internet of Energy
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中文摘要
针对第四次智能工业革命的迅猛发展及向第五次第六次工业革命的快速演化，我们发展了
具有一般共性的资源配置博奕平台及其数学框架体系，它包含以量子计算量子计算机与区
块链技术为核心的将来量子云互联网、量子通信与能源电力系统等为实体的应用对象，可
用于具有多智能量子云计算服务池及多类队列用户对系统资源的基于深度卷积神经网络
（DCNN）学习的博奕竞争。在此平台系统中，其软件结构体系由区块链与量子区块链刻
画，所有用户都与自身的大数据流相关联对应，其随机动力的统计特征由三随机报酬更新
过程刻画。通过区块链量子区块链中的智能合约决策，每个用户可同时接受多个池的服务，
而每个拥有多服务器或多服务员的云计算池或量子云计算池也可同时服务于多个用户，这
些区块链中的智能合约决策可由一个博奕调度问题在每个时刻的瞬时纳什均衡点给出。为
了说明我们博奕平台的有效性，在我们所设计的资源调度策略之下，我们用具有机制转换
的反射扩散过程来刻画我们系统内部诸如队长与工作量过程等数据流的随机动力演化。通
过该扩散过程系统，在证明基于三随机报酬更新过程的泛函中心极限定理的基础上，我们
证明了我们所设计的资源调度策略是整个时轴上全局渐近Pareto对偶成本最优的纳什均衡
策略。另外，我们也设计了高维反射扩散过程仿真迭代算法并给出了相应的数值比较说明
我们所设计的智能合约策略的有效性。
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嘉宾主旨报告
- 该文中的主要学术成就是国际
大会及山西省科技大
讲堂等的特邀嘉宾大会主旨报告，其中量子云计算量子区块链与深度卷积神经网络学习智能博弈等成果是
第四次乃至第六次工业革命的核心关键技术，也是2018年世界数学家大会(ICM 2018)宣布的ICM 2022与ICM
2026所关心的焦点。同时，文中所设计虚拟现实服务也是当前热点领域元宇宙的原始核心技术，
点击这里参见戴万阳教授2021年11月12日应答江苏网记者的采访。
- The main results in the paper are presented as invited pleanry/keynote talks in international conferences.
The published achievements on quantum-cloud-computing, quantum blockchain, and smart game technologies
are the keys in the Fourth Industrial Revolution and even in the Sixth Industrial Revolution. They are also the
major focal points of ICM 2022 and ICM 2026, which were announced in ICM 2018.
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相关论文
- W. Dai, Quantum-computing with AI & blockchain: modelling, fault tolerance
and capacity scheduling
 , Mathematical and
Computer Modeling of Dynamical Systems, Vol. 25, No. 6, pp. 523–559, 2019 (SCI (Q2)).
- W. Dai, Optimal rate scheduling via utility-maximization for J-user MIMO Markov
fading wireless channels with cooperation ,
Operations Research, Vol. 61, No. 6, 1450-1462 (with additional 26 page proof of online e-companion ( Supplemental)),
2013 (SCI (Q1)).
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