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A novel algorithm of quantum random walk in server traffic control and task scheduling. (English) Zbl 1406.81019

Summary: 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 one \(m\)-dimensional quantum random walk into \(m\) one-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.

MSC:

81P68 Quantum computation
81S25 Quantum stochastic calculus
60G50 Sums of independent random variables; random walks
90B20 Traffic problems in operations research
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