Indoor RFID Network Planning by Different Intelligent Optimization Strategies

Authors

  • Fawzi M. Al-Naima
  • Shahad A. Yousif

Keywords:

RFID, network Planning, Intelligent Optimization Strategies, PSO, ACO, BCO, SMO, FPA, TSA

Abstract

Radio Frequency Identification (RFID) is a technique used for identification or tracking of objects. The fast development of RFID technology generates the most challenging RFID network planning (RNP) problem to cover all the tags in area by the readers with minimum cost. The optimization of RFID network becomes a necessary technique to minimize overall cost of RFID network. This paper presents different intelligent optimization strategies to distribute the minimum number of readers to cover all tags in a given area and define locations of readers in the RFID network. Six well known techniques have been studied; namely Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bee Colony Optimization (BCO), Flower Pollination Algorithm (FPA), Spider Monkey Optimization (SMO) and Tabu Search Algorithm (TSA). The algorithms are applied over three typical test areas, (10m×10m), (16m×12m) and (18m×14m) respectively. All methods for planning were implemented by building a Graphical User Interface (GUI) software tool using MATLAB. The GUI is used to input the dimensions of the required area and calculate the initial number of readers and tags which are distributed randomly in the area. The obtained results confirm that all the tested algorithms are promising for optimum planning of indoor RFID networks with different percentages in cost reduction reaching up to 55% in some cases.

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Published

2017-01-01

How to Cite

Fawzi M. Al-Naima, & Shahad A. Yousif. (2017). Indoor RFID Network Planning by Different Intelligent Optimization Strategies. Journal of Network and Innovative Computing, 5, 10. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/131

Issue

Vol. 5 (2017)

Section

Original Article

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