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IEEE Access

Entanglement-Based Competition Resolution in Distributed Systems

Sándor Imre, Marton Berces

Published Jan 1, 2021• 3 citations
Publisher

Abstract

Accessing scarce resources in distributed systems where entities are not centrally coordinated, whether roebucks are fighting for a doe or WiFi users are competing for a common radio channel, is associated with moderate efficiency and proves to be a challenging problem. In this study, we present our hypothesis on shared entanglement and how such a process can improve resource access in macroscopically distributed systems. Furthermore, the required entangled states can be established in a distributed manner.

DOI
10.1109/access.2021.3050271

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Accessing scarce resources in distributed systems where entities are not centrally coordinated, whether roebucks are fighting for a doe or WiFi users are competing for a common radio channel, is associated with moderate efficiency and proves to be a challenging problem. In this study, we present our hypothesis on shared entanglement and how such a process can improve resource access in macroscopically distributed systems. Furthermore, the required entangled states can be established in a distributed manner.
In the field of technology the competition for common resources has been with us for the last couple of decades. As systems become more complex newer and more efficient methods are needed to manage and possibly decrease the overhead caused by the competing entities. Advance in other fields like quantum computing can provide new methods to construct such algorithms. In this paper a full performance analysis is given on how a distributed systems resource access control mechanism performs with the proposed quantum-entanglement based algorithm.
Resource access is a fundamental challenge in distributed systems where multiple uncoordinated nodes contend for a limited medium. Classical random-access protocols, such as Slotted-ALOHA, achieve modest efficiency because of frequent collisions and retransmissions. An entanglement-based procedure for collision-free slot allocation is investigated in this paper. The performance is evaluated through simulation under ideal classical and quantum channels. A system of N competing nodes is modeled, and three operations are implemented: JOIN, LEAVE, and TRANSFER. These operations rebalance amplitude probabilities and reflect node priorities while preserving normalization. The entanglementbased approach compares the obtained throughput and collision metrics with those of Slotted-ALOHA. It is shown through simulation results that higher throughput is achieved and collisions are completely eliminated across all testedNNNand iteration settings. According to the theoretical model presented in [9], this study is focused on developing a practical simulation framework and exploring priority-aware scenarios. The results demonstrate the feasibility of distributed entanglement establishment and provide a practical interpretation of JOIN, LEAVE, and TRANSFER operations under normalized probability constraints.
This paper proposes a novel approach to distributed memory access leveraging the principles of quantum entanglement entropy. The core idea is to utilize entanglement entropy to efficiently coordinate and route memory access requests, mitigating the latency and bandwidth bottlenecks associated with traditional global consistency models. We construct a quantum entanglement network connecting multiple computing nodes, enabling them to share entangled states. The entropy of these entangled states serves as a metric for determining which nodes possess the desired data. This allows for a fundamentally different, quantum-physical based coordination mechanism, moving beyond the complexity of conventional routing algorithms and consistency protocols. The proposed system aims to achieve significantly reduced access times and improved network utilization by exploiting the inherent correlations provided by quantum entanglement. The theoretical framework and key concepts are presented, outlining the potential for a substantial improvement in distributed memory system performance. The central equation describing the entanglement entropy-based routing is: E=∑i=1K∣si∣2E = \sum_{i=1}^{K} |s_i|^2E=∑i=1K​∣si​∣2, where EEE is the entanglement entropy, and sis_isi​ represents the state of the iii-th entangled qubit. This equation defines the entropy value as the sum of the squared magnitudes of the states of the entangled qubits. Furthermore, the probability of a node possessing the required data is proportional to the entanglement entropy: P(nodei)=Ei∑j=1KEjP(node_i) = \frac{E_i}{\sum_{j=1}^{K} E_j}P(nodei​)=∑j=1K​Ej​Ei​​. The system's performance is analyzed considering the number of entangled qubits (KKK), the entanglement fidelity, and the access latency. We explore potential optimizations and scaling strategies for large-scale distributed systems.
This paper proposes a novel approach to distributed computing heterogeneity optimization driven by quantum entanglement. Traditional distributed computing systems face significant challenges in efficiently utilizing diverse computing resources, leading to performance bottlenecks. We introduce a framework that leverages the unique properties of quantum entanglement to establish a quantum entanglement network, enabling high-fidelity, low-latency communication and computation across heterogeneous nodes. The core idea involves distributing computational tasks across these nodes based on their specific capabilities, utilizing entangled states to facilitate efficient data exchange and collaborative processing. The theoretical framework is presented, outlining the key mathematical concepts and optimization strategies. We demonstrate the potential of this approach to overcome the limitations of conventional methods and achieve significant improvements in distributed computing performance. The proposed system utilizes entanglement to achieve a level of computational coordination previously unattainable, offering a fundamentally new paradigm for distributed problem-solving. The focus here is on the theoretical foundations and potential benefits of the entanglement-based approach.
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This paper explores a novel approach to distributed computing resource scheduling leveraging the principles of quantum entanglement. Traditional distributed computing systems face limitations in efficiency and security due to reliance on classical communication and shared states, which are susceptible to interference and vulnerabilities. This research proposes a system where each computing node generates and shares a quantum entangled state with other nodes. By encoding and measuring these entangled states, we can indirectly control the state of remote nodes, enabling dynamic resource allocation and parallel task execution. Critically, this approach provides inherent security through the reliance on entangled states for communication and control, eliminating the need for traditional cryptographic mechanisms. We present a theoretical framework and explore the potential benefits of this system, highlighting its capacity to improve computational efficiency and data security while addressing limitations of current distributed computing paradigms. The core claim is that utilizing quantum entanglement enables efficient and secure distributed resource scheduling, while the core mechanism involves creating shared entangled states and leveraging their measurement for control.