Affiliation:
1. Network Center, Qingdao Technological University, Qingdao 266033, China
2. College of Automobile and Transportation, Qingdao Technological University, Qingdao 266033, China
Abstract
A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose onem-dimensional quantum random walk intomone-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm), ACO (ant colony optimization), and SAA (simulated annealing algorithm). In the same time, we prove its validity and rationality by the experiment of analog and simulation.
Funder
National Natural Science Foundation of China
Cited by
3 articles.
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1. Quantum walks-based classification model with resistance for cloud computing attacks;Expert Systems with Applications;2023-12
2. Efficient quasi-Monte Carlo sampling for quantum random walks;APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 12th International On-line Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’20;2020
3. A study and analysis of a discrete quantum walk-based hybrid clustering approach using d-regular bipartite graph and 1D lattice;International Journal of Quantum Information;2019-03