Smooth is better than sharp: a random mobility model for simulation of wireless networks

By Christian Bettstetter. International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2001

545 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/92044525efee82119be38c9280764e902f942fde

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Mobile ad hoc networking: imperatives and challenges (2003, background): “Nodes moving according to the random waypoint model tend to concentrate in the middle of the simulated area, creating the so-called border effect [14,15,37].”
Stationary distributions for the random waypoint mobility model (2004, unknown): “A variant of the random waypoint mobility model is presented in [12], but the stationary distribution for this model differs from the uniform as well.”
PATHS: analysis of PATH duration statistics and their impact on reactive MANET routing protocols (2003, unknown): “Stochastic properties of the RW model were studied recently in [20], [21] and [22].”
Data MULEs: modeling a three-tier architecture for sparse sensor networks (2003, methodology): “We hope to develop a more sophisticated stochastic model which can incorporate more generalized mobility models such as Smooth Random Mobility Model [18] or Brownian motion with drift [19], [20].”
The Spatial Node Distribution of the Random Waypoint Mobility Model (2002, background): “In a previous paper [ Bet01 ], we noted that it is important to realize that the choice of the mobility model determines the resulting spatial node distribution during simulation.”
Vehicular Mobility Simulation for VANETs (2007, unknown): “The Graph-Based Mobility Model (GBMM) [40], the Constant Speed Motion (CSM) [2] and the Smooth Motion Model (SMM) [41] fall into the first category, as the speed of each vehicle is determined on the basis of the local state of each car and any external effect is ignored.”
An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces (2006, background): “Many of the ad hoc network studies use random way point, random directions, and other models where the nodes change their speed and direction randomly [3,7,8,29].”
A SURVEY OF MOBILITY MODELS in Wireless Adhoc Networks (2004, background): “In Ref.”
An integrated mobility and traffic model for vehicular wireless networks (2005, unknown): “Others have attempted to more realistically simulate motion in RWP; in [3], for example, the authors introduce acceleration and deceleration near the waypoints.”
Modeling mobility for vehicular ad-hoc networks (2004, unknown): “Bettstetter [3] modified this model so that instead of suddenly changing to a new random speed after a node has reached a destination, the node accelerates to reach the target speed, and before reaching the destination, the node decelerates to come to a halt.”
A new networking model for biological applications of ad hoc sensor networks (2006, methodology): “We use a simple mobility pattern, the random linear mobility, which is a variant of the random waypoint model [4] with pause time 0.”
Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks (2003, methodology): “We hope to develop a more sophisticated stochastic model which can incorporate more generalized mobility models such as Smooth Random Mobility Model [18] or Brownian motion with drift [19] [20].”
Stochastic Properties of the Random Waypoint Mobility Model (2004, unknown): “Researchers in this area can choose from a variety of models that have been developed in the wireless communications and mobile computing community during the last decades [4, 13, 18, 22, 29].”
The ONE simulator for DTN protocol evaluation (2009, background): “Node velocity and pause times may be adjusted to match pedestrians, vehicles, or other node types and smooth turns, acceleration and deceleration may be added to obtain more realistic behavior [1].”
Resource and performance tradeoffs in delay-tolerant wireless networks (2005, methodology): “Although many different mobility patterns could be used, we chose the random directional mobility, similar to the pattern described by Bettstetter [2], on a closed (toroidal) network area.”