Abstract

We establish a generic system model with supply and demand sides for quantum economical systems with quantum cloud computing and federated learning, which can be used to model the future Internet with blockchain communication protocol and generalized Internet of Things (IoT) with smart resource allocations (Refs. [2]-[4]). We map the two sides via blockchain and control the internal data flow interactions via smart contracts by deep convolutional neural network (DCNN) oriented game-theoretic pooling policies with symmetry or asymmetry information, where federated learning algorithms with small data training are designed. The pooling is with two levels of competitions (i.e., greedy and optimal sharing competitions) corresponding to a mixed zero-sum and non-zero-sum game with general number of players. In formulating our model, there are three aspects: system hardware modeling via (quantum) cloud-computing, system software modeling via blockchain, big data flow modeling via generalized stochastic models. The focus of our study is on the interaction and integration of the three aspects. The effectiveness of our policies is proved by stochastic modeling with theory and simulation examples. This project is innovative since our generic model is new, our dynamic policy is new, and our big data flow modeling is new. As claimed by SIR Forum (Ref. [1]), quantum computing and blockchain will be the core technology in the coming Sixth Industrial Revolution (SIR). Thus, our generic model is important in modeling the quantum economic systems that require synchronized multi-item services, e.g., the future Internet with blockchain communication protocol and supply chain finance (e.g., assemble to order (ATO)) systems. Besides, our generic model can also be implemented in the currently developing cognitive radio, 5G/6G, IoE, FinTech, and health-care systems.

Introduction

We establish a generic system model with supply and demand sides for quantum economical systems with quantum cloud computing and federated learning, which can be used to model the future Internet with blockchain communication protocol and generalized Internet of Things (IoT) with smart resource allocations (Refs. [2]-[4]). We classify our generic model into supply and demand sides as in a macro-economic system (Ref. [2]). The supply-side can be a general information network while demand-side can consist of various things with general infrastructure (e.g., an energy grid or a supply chain). We map the two sides via blockchain and control the internal data flow interactions via smart contracts by deep convolutional neural network (DCNN) oriented game-theoretic pooling policies with symmetry or asymmetry information, where federated learning algorithms with small data training are designed by mixed zero-sum and non-zero-sum game-theoretic policies. Each zero-sum or non-zero-sum game is further associated with two coupled utility-maximization and cost-minimization dual games with general number of players. In formulating our generic model, there are three aspects: system hardware modeling via quantum cloud-computing, system software modeling via blockchain, big data flow modeling via general-dimensional stochastic models such as triply stochastic renewal reward process driven stochastic networks (Refs. [3]-[4]). The focus of our study is on the interaction and integration of the three aspects. When the quantum-computing is involved, we design a quantum-computing chip by modeling it as a multi-input multi-output (MIMO) quantum channel as in the MIMO wireless mobile computing (e.g., in 5G/6G). To capture our system's internal bit or qubit data flow dynamics, we model it via a deep convolutional neural network (DCNN) with generalized stochastic pooling in terms of resource-competition among different antennas and quantum eigenmodes or users. The pooling is with two levels of competitions: the first one is on users' selection in a "win-lose" manner; the second one is on resource-sharing among selected users in a "win-win" manner. The effectiveness of our policies is proved by stochastic modeling with theory and simulation examples. This project is innovative since our generic system is new, our dynamic policy is new, and our big data flow modeling is new. Furthermore, as claimed by SIR Forum, quantum computing and blockchain will be the core technology in the coming Sixth Industrial Revolution (SIR). Thus, our generic model is important in modeling the quantum economic systems that require synchronized multi-item services, e.g., the future Internet with blockchain communication protocol and supply chain finance (e.g., assemble to order (ATO)) systems (Refs. [3]-[4]). In addition, our model can also be implemented in the currently developing cognitive radio, 5G/6G, internet of energy (IoE), FinTech, and health-care systems. Due to these facts, Wanyang Dai was elected to be the (2019 and 2020) President & CEO of SIR Forum (Ref. [1]) and was honorably invited to be the keynote speakers of various IEEE and other international conferences. His influential findings and inventions received various awards and were published by well-known journals such as Operations Research, etc. (Refs. [3]-[5]).

Analytics Components

For the descriptive aspect, we have established a generic model to describe the quantum economical systems (e.g. the future Internet with blockchain communication protocol and the generalized IoT system) (Refs. [2]-[4]) with three aspects. For the predictive aspect, we have developed theory to effectively justify our general-dimensional stochastic models to present the data flow dynamics in our generic model. Based on these stochastic models, we have conducted numerical and statistical simulation to justify the advantages of dynamical policies (Refs. [3]-[4]). For the prescriptive aspect, we model our system's internal data flow dynamics via a DCNN with generalized stochastic pooling in terms of resource-competition (Refs [3]-[5]) to realize smart contracts within a blockchain.

Conclusion

Our generic system model is important for modeling the future Internet with blockchain communication protocol (Refs. [3]-[4]). It can also be implemented in the quickly developing cognitive radio, 5G/6G, IoE, FinTech, supply chain, and health-care systems. Owing to these facts, Wanyang Dai was elected to be the (2019 and 2020) President & CEO of SIR Forum (Ref. [1]) and was honorably invited to be the keynote speakers of various IEEE and other international conferences such as 2017 IEEE 7TH International Conference on Power and Energy System in Toronto, 2019 International Conference on Future Advancements of Mobile Cloud Computing and Applications in Toronto, and 2020 IEEE International Conference on Artificial Intelligence and Computer Engineering in Beijing. Besides, he was also honorably invited to give guest speech in People's Bank of China concerning FinTech and InsurTech.

References

[1] SIR Forum with website at https://www.sirforum.net/ was founded in Los Angeles on February, 2018, which is a global non-profit organization dedicated putting synergy to enable and lead the Sixth Industrial Revolution powered by blockchain and quantum computing technologies, with members from scientists, engineers, entrepreneurs, and investors in the blockchain and quantum computing industries around the world.
[2] Wanyang Dai is with the projects "Optimal resource competition game and equilibrium controls in Generalized Internet of Things driven by Big Data and smart cloud computing" and "Stochastic systems and optimal resource-performance controls in future wireless communication networks", which are supported by Natural Science Foundation of China (NSFC) from 2018 to 2021 and from 2014 to 2017 respectively.
[3] Wanyang Dai, "Platform modeling and scheduling game with multiple intelligent cloud-computing pools for Big Data", Mathematical and Computer Modeling of Dynamical Systems 24(5) 506-552, 2018
[4] Wanyang Dai, "Quantum-Computing with AI & Blockchain: Modeling, Fault Tolerance, and Capacity Scheduling", Mathematical and Computer Modeling of Dynamical Systems 25(6) 523-559, 2019.
[5] Wanyang Dai, "Optimal rate scheduling via utility-maximization for J-user MIMO Markov wireless channels with cooperation", Operations Research 61(6) 1450-1462 (with additional 26 page proof of online e-companion (Supplemental)), 2013.