- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
It is widely known that the instantaneous average node speed for the random waypoint (RWP) mobility model may not reach a steady state regime due to velocity gradual decaying which can cause inaccurate results in simulations and communication protocol validations for wireless networks. This paper presents a modification to the RWP model, in which we propose to choose node speeds from a BETA(α, β) distribution, demonstrating analytically and by simulations that depending on the values of α and β parameters the instantaneous average node speed and consequently other important network metrics, like control overhead and number of dropped data packets may reach (or not) a steady state regime. Therefore, by allowing α and β to vary, a multitude of probability distributions for speed choice is obtained and the resulting limiting state behavior for the mobility model can straightforwardly be determined, offering to the research community a generalized BETA random waypoint mobility model. Accordingly, the generic analytical closed form for the instantaneous average node velocity V as Vmin →0 is obtained as a function of α and β to be given by limVmin→ 0 V = Vmax α−1 β+α−1 in which Vmin and Vmax are the minimum and maximum velocities, respectively, that a node can select.
This paper proposed and analyzed a modification that stabilizes the random waypoint mobility model used to evaluate performance of mobile wireless networks. We showed that the use of a BETA(α, β) distribution for choosing node speed, results a steady state expected node speed equals to Vmax α−1 β+α−1 as Vmin → 0. Therefore, by choosing α ≥ 2, it avoids the gradual decaying with time of the instantaneous average node speed when the minimum velocity in the choice range is set to zero. On the other hand, if α = 1, irrespective of the value of β, the instantaneous average speed decays to zero. Analytical and simulation results were presented which showed the impact of instantaneous average node speed in network performance metrics. Beyond providing a RWP mobility model spanning a multitude of speed distributions, our investigation corroborates the importance of using a stable mobility model when communication protocols are under evaluation in wireless networks. Future work can extend our analysis to consider changing the BETA Random Waypoint model to address the node concentration issue, as well as to investigate its behavior in other network topologies like circle, torus and sphere.