Abstract Because of the sustained growth of information and mobile users transmitting a great amount of data packets, modern network performances are being seriously affected by congestion problems. In fact, congestion management is a challenging task that can be roughly summarized as a trade off between transmission latency and cost. In this context, a novel framework is proposed for solving the congestion problem on communication networks using a quantum game theory model, where network packets compete selfishly for the shortest route. Simulations show that final network routing and traveling times achieved with the quantum game version outperform those obtained classically. This leads to the opportunity of developing full-stack protocols that may be capable of taking advantage of the quantum properties for optimizing communication systems. Due to its generality, the game theoretic approach can be applied both in local networks and in more complex networks such as 5G or LTE-A.
Abstract Because of the sustained growth of information and mobile users transmitting a great amount of data packets, modern network performances are being seriously affected by congestion problems. In fact, congestion management is a challenging task that can be roughly summarized as a trade off between transmission latency and cost. In this context, a novel framework is proposed for solving the congestion problem on communication networks using a quantum game theory model, where network packets compete selfishly for the shortest route. Simulations show that final network routing and traveling times achieved with the quantum game version outperform those obtained classically. This leads to the opportunity of developing full-stack protocols that may be capable of taking advantage of the quantum properties for optimizing communication systems. Due to its generality, the game theoretic approach can be applied both in local networks and in more complex networks such as 5G or LTE-A.
Because of the sustained growth of information and mobile users transmitting a great amount of data packets, modern network performances are being seriously affected by congestion problems. In fact, congestion management is a challenging task that can be roughly summarized as a trade off between transmission latency and cost. In order to contribute to solve the congestion problem on communication networks, a novel framework based on a quantum game model is proposed, where network packets compete selfishly for their fastest route. Simulations show that final network routing and traveling times achieved with the quantum version outperform those obtained with a classical game model with the same options for packet transmission for both. Pareto optimality and Nash equilibrium are studied as well as the influence of simulated and real noise in the quantum protocol. This leads to the opportunity of developing full-stack protocols that may be capable of taking advantage of the quantum properties for optimizing communication systems. Due to its generality, this game approach can be applied both in classical complex networks and in future quantum networks in order to maximize the performance of the quantum internet.
With the imminent advent of quantum communications head-on and its landing in what is going to be called the Quantum Internet, it is essential to research different ways of how it could be done in its most efficient way. In this work, we propose a game theory based self-adaptive system that, by accumulating reward, manages to learn how to minimize the latency of packets that are sent in a congested quantum network. To begin with, we study under which circumstances the quantum protocol outperforms its classical equivalent. First, analyzing the minimum number of packets moving through the network as a function of the size of the network necessary for guaranteeing an improvement in the quantum protocol. Then, studying the minimum size of the network based on the number of nodes needed to ensure the aforementioned advantage. Furthermore, taking advantage of the concepts of non-cooperative games and reinforcement learning, a protocol is designed and the behavior of a network with quantum nodes is evaluated. In order to analyze this protocol, different algorithms and scenarios are tested by measuring their efficiency and adaptability.
Classical game theory is a powerful tool focusing on optimized resource distribution, allocation, and sharing in classical wired and wireless networks. As quantum networks are emerging as a means of providing true connectivity between quantum computers, it is imperative and crucial to exploit game theory for addressing challenges such as entanglement distribution and access, routing, topology extraction, and inference. Quantum networks provide the promising opportunity of employing quantum games owing to their inherent capability of generating and sharing quantum states. In addition, quantum games offer enhanced payoffs and winning probabilities, new strategies, and equilibria, which are unimaginable in classical games. Employing quantum game theory to solve fundamental challenges in quantum networks opens a new fundamental research direction necessitating inter-disciplinary efforts. In this article, we introduce a novel game-the-oretical framework for exploiting quantum strategies to solve – as an archetypal example – one of the key functionalities of a quantum network, namely, entanglement distribution. We compare quantum strategies with classical ones by showing the quantum advantages in terms of link fidelity improvement and latency decrease in communication. In the future, we will generalize our game framework to optimize entanglement distribution and access over any quantum network topology. We will also explore how quantum games can be leveraged to address other challenges like routing, optimization of quantum operations, and topology design.
This paper proposes a novel approach to network routing leveraging the unique properties of quantum entanglement. Traditional network routing relies on physical distances and delays, presenting inherent limitations in bandwidth and latency. This research posits that quantum entanglement can be harnessed to overcome these constraints, enabling ultra-high bandwidth and low-latency data routing. The core concept involves constructing a "quantum network" composed of entangled qubits, enabling efficient data transmission and routing via precise control of the entangled states. We explore and develop algorithms designed to minimize entanglement loss and latency, crucial factors in realizing the full potential of this technology. The theoretical framework presented here introduces a fundamentally new paradigm for network architecture, moving beyond classical constraints and towards a quantum-enhanced communication infrastructure. The primary focus is on the theoretical design and optimization of routing protocols specifically tailored for entangled quantum networks. We outline a methodology for simulating and optimizing quantum routing algorithms, acknowledging the challenges associated with decoherence and entanglement degradation. This work establishes a foundation for future research and development in quantum networking and routing.
Quantum nodes exchange qubits to achieve largescale quantum computing applications in a quantum network (QN). However, due to environmental influences, entangled links used for data transmission would decohere over time. Besides, the scarcity of quantum memory in each quantum node necessitates frequent communication between nodes, leading to significant variations in the traffic matrix. Thus, providing real-time services in QNs becomes particularly important. To this end, this paper presents a new optimization problem and proposes a novel online algorithm, which combines the game-theoretic analysis results with the linear programming (LP) by the primal-dual technique. Finally, the simulation results demonstrate that the proposed algorithm outperforms the other baselines by up to 90 %.
Over recent years, quantum communication systems have demarcated themselves as promising candidates for deployment in next-generation communication networks (6G and beyond). Several recent experimental demonstrations of such complex systems have been highly successful and have been instrumental in transitioning this field from the theoretical to the practical domain. In this article, we investigate the application of quantum game theory for the modeling and analysis of jamming in the context of quantum networks. We begin with a general model of jamming based on the Colonel Blotto game and generalize it to the context of quantum networks. We provide an in-depth analysis of the two-person quantum Colonel Blotto game (QCBG) in relation to classical versus classical, classical versus quantum, and quantum versus quantum strategies. We also investigate the Nash equilibria for such games via a multiagent adversarial reinforcement learning-based system. Finally, we discuss further optimizations on this model and outline several open problems for further research along these lines.