Evaluating the feasibility of random waypoint model for indoor wireless networks

Sihua Shao, Abdallah Khreishah, Moussa Ayyash

Research output: Contribution to journalLetterpeer-review

2 Scopus citations


Trace-driven simulations supported by long-term and human-based indoor mobility traces are able to properly validate the effectiveness and efficiency of the algorithms, protocols or applications utilized in indoor wireless networks. Nevertheless, most of the mobility models adopted in the existing works are simplified variations of random waypoint (RWP) model. To evaluate the feasibility of RWP model, we extract the real-time mobility trace of a one-month period human-based raw dataset and quantitatively compare the extracted trace to that of RWP model. The comparison results reveal the inaccuracy of RWP model. We also evaluate the use of the indoor mobility trace while studying different mobility-aware problems of indoor wireless networks.

Original languageEnglish (US)
Article numbere214
JournalInternet Technology Letters
Issue number2
StatePublished - Mar 1 2021

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications


  • human-based dataset
  • indoor
  • mobility trace
  • random waypoint model
  • wireless networks


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