Year: 2024
Type: article
Abstract: This analytical article rigorously evaluates the revolutionary capacity of quantumcomputing in enhancing network traffic optimisation and data routing, a field historicallycontrolled by conventional techniques. Due to the rapid expansion of data and the growingintricacy of network infrastructures, traditional methods are frequently constrained by theirinadequate capacity to effectively scale and oversee resources. Quantum computing, utilising theconcepts of superposition and entanglement, presents a hopeful solution to surpass theseconstraints by offering unparalleled processing capability and efficiency.The study starts by examining the fundamental concepts of quantum physics that serve as thefoundation of quantum computing. Superposition permits quantum bits (qubits) to concurrentlyembody and manipulate several states, whereas entanglement facilitates the interconnection ofqubits that are physically apart, hence enabling expedited and more intricate computations. Thesefeatures offer substantial benefits compared to classical bits, which are limited to binary states.We explore the precise quantum algorithms that have the ability to optimise networks, with aparticular focus on Grover's search algorithm and the Quantum Approximate OptimisationAlgorithm (QAOA). The Grover's technique provides a quadratic improvement in searchprocedures, enabling more efficient identification of optimal pathways in routing issues.Conversely, QAOA is well-suited for handling combinatorial optimisation issues, namely thosefound in network traffic management.A comprehensive analysis of current literature and case studies is performed to assess the practicaluses of quantum algorithms in network contexts. Metrics such as reducing latency, optimisingbandwidth utilisation, minimising packet loss, and effectively managing congestion are closely examined. Our study suggests that quantum computing has the potential to greatly improve theseperformance indicators. Quantum algorithms have the capability to handle large quantities of datasimultaneously, resulting in quicker identification of the best routes and more effective trafficcontrol. This leads to reduced latency and enhanced total network performance.The report also evaluates the existing technological and theoretical obstacles that impede themainstream implementation of quantum computing in network management. Important concernsencompass the reliability and consistency of qubits, the ability to repair errors, and the capacityfor quantum systems to be expanded. Furthermore, this study investigates the infrastructuralobstacles, such as the requirement for specialised hardware and the incorporation of quantumsystems into current network topologies. We emphasise the continuous progress in quantumtechnology, including the enhancement of qubits' stability and the refinement of quantum errorcorrection techniques, both of which are crucial for tackling these difficulties.Moreover, the research examines the possible long-term consequences of quantum computing onnetwork management paradigms. Quantum computing offers substantial enhancements inprocessing speed and efficiency, as well as presents novel approaches for solving complicatedoptimisation problems that are currently unsolvable using traditional methods. Our proposalinvolves investigating future research areas, specifically focusing on the advancement of hybridquantum-classical algorithms and the examination of quantum machine learning approaches foradaptive network management.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7216625201