Building Sound Mobility Models for AD HOC Network Simulation

Abstract

The design and evaluation of mobile ad hoc network research often heavily relies on simulations of the system. Underlying the simulation is the mobility model that generates the movement of the constituents of the network. In order to obtain accurate and reliable performance results, we need these mobility models to be suitable for simulation studies. In order to apply simulation results to practice, we also need these mobility models to be reasonably realistic in representing the actual movement of human or vehicles. Motivated by these requirements, in addressing the first need in this project we derive a general framework within which we construct stationary random mobility models that are suitable for simulation studies in that no warm-up is needed as the mobility models start in steady state. In doing so we also illustrate the flaws with existing mobility models, as well as ways in which they are typically used. In addressing the second need we construct realistic mobility models from real data traces collected over a college campus. Such models combine mobility data with geographical data (campus map, road/building information, etc.), and more closely capture real movement than random mobility models that are commonly used. Technical approaches used in this project include stochastic modeling, renewal theory and computer simulation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2005
Accession Number
ADA437092

Entities

People

  • Mingyan Liu

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Ad Hoc Networks
  • Air Force Research Laboratories
  • Computer Simulations
  • Computers
  • Computing System Architectures
  • Mesh Networks
  • Mobile Ad Hoc Networks
  • Network Architecture
  • Network Simulation
  • Networks
  • Probability
  • Simulations
  • Simulators
  • Stationary
  • Stationary Processes
  • Steady State
  • Stochastic Processes

Fields of Study

  • Computer science

Readers

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