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Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System.

Litian Duan1, Zizhong John Wang2,3, Fu Duan4

  • 1College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, China. duanlitian0030@link.tyut.edu.cn.

Sensors (Basel, Switzerland)
|November 18, 2016
PubMed
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This summary is machine-generated.

This study introduces a new algorithm for scheduling radio frequency identification (RFID) readers in busy environments. The Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) ensures fair resource allocation for better performance.

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Artificial Intelligence

Background:

  • Radio Frequency Identification (RFID) systems face challenges in multiple-reader environments (MRE) due to signal interference.
  • Efficient scheduling of multiple readers is crucial to mitigate interference and optimize performance.

Purpose of the Study:

  • To propose a novel algorithm, GD-MRSOA-AIS, for fair and optimal scheduling of RFID readers in MRE.
  • To enhance resource allocation and improve the effective interrogation range of RFID systems.

Main Methods:

  • Developed a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS).
  • Incorporated a geometric distribution function with fairness considerations to generate feasible scheduling schemes.
Keywords:
geometric distribution probability functionmultiple-reader environmentmultiple-reader interferenceoptimization by artificial immune system

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  • Utilized artificial immune system mechanisms (cloning, mutation, suppression) for optimizing scheduling schemes.

    • Main Results:

    • GD-MRSOA-AIS demonstrated efficient scheduling of multiple RFID readers.
    • The algorithm achieved fairer resource allocation compared to existing methods.
    • Simulation results showed an increased effective interrogation range.

    Conclusions:

    • GD-MRSOA-AIS provides an effective solution for optimizing RFID reader scheduling in MRE.
    • The proposed algorithm ensures fair resource distribution, leading to improved system performance and range.