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International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)

Performance Analysis of Entanglement-based Competition Resolution in Distributed Systems

Marton Berces, Sándor Imre, Andras Prakfalvi

Published Jul 1, 2018• 0 citations
Publisher

Abstract

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.

DOI
10.1109/csndsp.2018.8471815

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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.
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This paper proposes a novel approach to distributed computing resource scheduling leveraging the unique properties of quantum entanglement. Traditional resource scheduling methods suffer from inefficiencies and high latency due to reliance on classical communication. Our framework utilizes entangled states between computational nodes to enable efficient task allocation, rapid data transfer, and real-time resource monitoring. The core claim is that exploiting the non-local nature of entanglement can overcome the limitations of current methods. The proposed mechanism involves constructing a quantum entanglement-based resource scheduling system, facilitating parallel task execution and high-speed data transmission. Mathematical models are presented to illustrate the potential performance gains and key considerations for this approach. This research contributes to the emerging field of quantum computing and offers a promising avenue for optimizing distributed computing systems.
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