Earticle

초록

영어

Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimization-based IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.

목차

Abstract
 1. Introduction
 2. Background Study
  2.1. The Multi-objective Fitness Function
  2.2. The Optimization Algorithms
 3. The Proposed Approaches
  3.1. The Advanced Multi-objective Fitness Function
  3.2. The Proposed Improved Genetic Annealing Algorithm (IGAA)
 4. Experimental Evaluation
 5. Conclusions
 Acknowledgement
 References

키워드

저자

• Po-Jen Chuang [ Department of Electrical Engineering Tamkang University Tamsui, New Taipei City, Taiwan 25137, R. O. C. ]
• Wei-Ting Tsai [ Department of Electrical Engineering Tamkang University Tamsui, New Taipei City, Taiwan 25137, R. O. C. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605