Abstract
In industrial Internet, many intelligent applications are implemented based on data collection and distribution. Data collection and data distribution in the wireless sensor networks are very important, where the node topology can be described by the spanning tree for obtaining an efficient transmission. Classical algorithms in graph theory such as the Kruskal algorithm or Prim algorithm can only find the minimum spanning tree (MST) in industrial wireless sensor networks. Swarm intelligence algorithm can obtain multiple solutions in one calculation. Multiple solutions are very helpful for improving the reliability of industrial wireless sensor networks.In this paper, we combine quantum computing with artificial bee colony and design a spanning tree construction algorithm for industrial wireless sensor networks. Quantum computations are introduced into the onlooker bees search. Food source replacement strategy is improved. Finally, the algorithm is simulated and evaluated. The results show that the new proposed algorithm can obtain more alternative solutions and has a better performance in search efficiency.
Highlights
IntroductionWireless sensor networks (WSN) (wireless sensor networks) [1, 2] is an autonomous measurement and control network system that consist of a large number of ubiquitous, small sensor nodes with communication and computing capabilities that are densely deployed in unattended monitoring areas [3]
1 Introduction Wireless sensor networks (WSN) [1, 2] is an autonomous measurement and control network system that consist of a large number of ubiquitous, small sensor nodes with communication and computing capabilities that are densely deployed in unattended monitoring areas [3]
In the evolutionary process of swarm intelligence algorithm [25,26,27], a series of solutions are generated, which is very suitable for the solution of the spanning tree problem in Industrial Wireless Sensor Networks environment
Summary
WSN (wireless sensor networks) [1, 2] is an autonomous measurement and control network system that consist of a large number of ubiquitous, small sensor nodes with communication and computing capabilities that are densely deployed in unattended monitoring areas [3]. This is generally called the data collection protocol [20, 21] The control information such as commands for monitoring the industrial field devices is performed through another protocol. In the evolutionary process of swarm intelligence algorithm [25,26,27], a series of solutions are generated, which is very suitable for the solution of the spanning tree problem in Industrial Wireless Sensor Networks environment. There are already some classical algorithms for solving the minimum spanning tree in graph theory, such as Kruskal algorithm or Prim algorithm These algorithms can only get one solution at a time. Swarm intelligence algorithm to obtain multiple solutions at a time just can effectively solve this requirement of industrial wireless sensor networks. This paper will use the artificial bee colony algorithm and use the idea of quantum computing to solve this problem
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