Title: Virtual resource mapping in wireless sensor networks based on the maximum independent link set

Authors: Danjun Deng

Addresses: Computer Science Department, Hubei PolyTechnic University, Huangshi, 435003, China

Abstract: To solve the problems of low mapping success rate, high mapping energy consumption, and low conversion rate of high-dimensional data existing in traditional methods, this paper proposes a virtual resource mapping method based on the maximum independent link set. A vector space model to reduce the dimensionality of the virtual wireless sensor networks (WSNs) resource data was adopted. A support vector machine to input the dimensionality reduction results into the resource feature space for resource classification to obtain the independent link set and label in virtual links of the WSNs was also adopted. According to the maximum independent link set, we design the network virtual resource mapping process to complete the resource mapping. Experimental results show that, compared with other methods, our method has a higher success rate of resource mapping, lower energy consumption, and higher conversion rate of high-dimensional data.

Keywords: maximum independent link set; WSNs; wireless sensor networks; virtual resource mapping; resource classification; label the semantic.

DOI: 10.1504/IJSNET.2022.122984

International Journal of Sensor Networks, 2022 Vol.39 No.1, pp.34 - 40

Received: 03 Aug 2021
Accepted: 03 Aug 2021
Published online: 19 May 2022 *

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