Gamma random waypoint mobility model for wireless ad hoc networks

Abstract

SUMMARYRandom waypoint (RWP) mobility model is widely used in ad hoc network simulation. The model suffers from speed decay as the simulation progresses and may not reach the steady state in terms of instantaneous average node speed. Furthermore, the convergence of the average speed to its steady state value is delayed. This usually leads to inaccurate results in protocol validation of mobile ad hoc networks modeling. Moreover, the probability distributions of speed vary over the simulation time, such that the node speed distribution at the initial state is different from the corresponding distribution at the end of the simulation. In order to overcome these problems, this paper proposes a modified RWP mobility model with a more precise distribution of the nodes' speed. In the modified model, the speeds of nodes are sampled from gamma distribution. The results obtained from both analysis and simulation experiments of the average speed and the density of nodes' speed indicate that the proposed gamma random waypoint mobility model outperforms the existing RWP mobility models. It is shown that a significant performance improvement in achieving higher steady state speed values that closely model the pre‐assumed average speeds are possible with the proposed model. Additionally, the model allows faster convergence to the steady state, and probability distribution of speed is steady over the simulation time. Copyright © 2012 John Wiley & Sons, Ltd.

Endcast: mobile stateless data delivery in MANETs

“…After reaching the determined waypoint it waits for a time duration, normally distributed between a minimum and a maximum, and repeats the process with next selected waypoint [36]. If the target application scenario is for human mobility as in the case of managing a disaster relief camp, minimum and maximum speeds are selected as 1 to 2 m/s and the pause time is between 0 and 0.5 s. These values are in line with similar studies that capture human mobility scenarios [35][36][37][38]. Figure 27 corresponds to a network density of 10 as defined in terms of average neighborhood per node.…”

“…Random Way Point (RWP) mobility is extensively applied in wireless network simulations [35][36][37][38]. In RWP mobility model, a node selects a random starting position and a random point in the area as the next waypoint.…”

The impact of node velocity diversity on mobile opportunistic network performance

“…So far, various mobility models are proposed to describe random movement patterns of nodes in ad hoc networks. Among them, the Random Way Point (RWP) mobility model Sabah and Hocanin, 2013, Random Walk (RW) mobility model (Cai et al, 2014;Aslam and Rashid, 2011) and Random Direction (RD) mobility model are the most typical and traditional random mobility models, and they have been widely applied in studying random movement features of individuals in the realistic environment and the performance of MANETs.…”

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“…The RWP mobility is extensively applied in wireless network simulations [7], [9], [21], [22]. In this mobility model a node selects a random starting position and a random location in the area as the next waypoint.…”