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SHER: a colored petri net based random mobility model for wireless communications.

Naeem Akhtar Khan1, Farooq Ahmad2, Sher Afzal Khan3

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We introduce the Show Home and Exclusive Regions (SHER) model, a novel mobility model for wireless networks. SHER captures user behavior and improves network performance by addressing key limitations of existing random mobility models.

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Area of Science:

  • Computer Science
  • Wireless Communication Networks
  • Network Simulation

Background:

  • Simulation is crucial for wireless network research and validation.
  • Mobility models are essential for mimicking real-world user movement in simulations.
  • Existing random mobility models have several limitations affecting simulation accuracy.

Purpose of the Study:

  • To devise and evaluate a novel formal random mobility model called Show Home and Exclusive Regions (SHER).
  • To capture sociological user behavior, including frequent visits to specific locations (hotspots).
  • To address and resolve six key issues present in conventional random mobility models.

Main Methods:

  • Development of a two-dimensional (2-D) Colored Petri net (CPN) based formal random mobility model (SHER).
  • Incorporation of user sociological behavior, including the identification of 'show home' and 'exclusive regions' (hotspots).
  • Utilizing statistical and reachability analysis techniques for model validation and performance elucidation.

Main Results:

  • The SHER model successfully eliminates six critical issues: sudden stops, memoryless movements, border effect, temporal velocity dependency, pause time dependency, and speed decay.
  • The model can predict future user locations, leading to improved wireless communication network performance.
  • SHER provides a uniform nodal distribution and exhibits distinct mobility patterns, functioning as a mini-simulator.

Conclusions:

  • The SHER model offers a significant advancement in wireless network mobility modeling by integrating realistic user behavior.
  • The use of Colored Petri nets (CPN) for capturing dynamic mobility patterns is a challenging yet effective approach.
  • The model's ability to predict user movement and improve network performance validates its utility for researchers and practitioners.