期刊
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
卷 12, 期 2, 页码 2905-2914出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12652-020-02446-5
关键词
Radio frequency identification; Network planning; Constraint satisfaction problem
The rapid growth of industrial society requires large-scale deployment of radio frequency identification networks, and finding the optimal number, placement, and parameters of readers is crucial for providing high-quality service. Effective planning is essential for solving the radio frequency identification network planning problem.
The huge growth of industrial society requires the deployment of radio frequency identification networks on a large scale. This necessitates the installation of a large number of radio frequency identification components (readers, tags, middleware and others). As a consequence, the cost and complexity of networks are increasing due to the large number of readers to be installed. Finding the optimal number, placement and parameters of readers to provide a high quality of service for radio frequency identification systems is a critical problem. A good planning affords a basic need for radio frequency identification networks, such as coverage, load balance and interference between readers. This problem is famous in the literature as a radio frequency identification network planning problem. All the proposed approaches in the literature have been based on meta-heuristics. In this paper, we design a new algorithm, called the RNP-CSP algorithm based on the constraint satisfaction problem framework to solve the radio frequency identification network planning problem. The performance evaluation shows that the RNP-CSP algorithm is more efficient than (PSO)-O-2, GPSO and VNPSO-RNP.
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