Random Mobility Model Research Articles

A simulation study on the performance of Mobile IPv6 in a WLAN-based cellular network

We performed a simulative evaluation of Mobile IPv6 (MIPv6) via ns-2 for a scenario comprising up to three access routers and 30 mobile nodes that communicate in accordance with the IEEE 802.11 wireless LAN standard. We compare standard MIPv6 to a fast handoff procedure and analyze route optimization issues. We present results with respect to handoff latency, packet loss, end-to-end delay, signaling load, channel utilization, and bandwidth per station, and show how various traffic types like UDP CBR, VoIP, and TCP are affected by the handoffs. While some simulation results corroborate the intention of the protocol specification, other results give insights not easily gained without performing simulations. For example, we learned that (i) the fast handoff mechanism almost fully eliminates packet losses but only improves handoff latency in specific cases, (ii) the signaling load introduced by MIPv6 does not severely affect the performance, and (iii) in a shared environment like IEEE 802.11, traffic type can affect the handoff rate since in high-load situations router advertisements might get lost more frequently thereby `irritating' the handoff decision mechanism. As a challenge for future simulations we have identified the design of a random mobility model that allows good control of the handoff rate.

Mobility modeling in wireless networks

The movement pattern of mobile users plays an important role in performance analysis of wireless computer and communication networks. In this paper, we first give an overview and classification of mobility models used for simulation-based studies. Then, we present an enhanced random mobility model, which makes the movement trace of mobile stations more realistic than common approaches for random mobility. Our movement concept is based on random processes for speed and direction control in which the new values are correlated to previous ones. Upon a speed change event, a new target speed is chosen, and an acceleration is set to achieve this target speed. The principles for direction changes are similar. Finally, we discuss strategies for the stations' border behavior (i.e., what happens when nodes move out of the simulation area) and show the effects of certain border behaviors and mobility models on the spatial user distribution.

The peril of evaluating location management proposals through simulations

The challenge of supporting rapidly growing numbers of mobile users, while constrained by limited radio spectrum, is being faced by cellular network operators worldwide. Several location management schemes have been proposed to improve the performance of such networks, but a fair assessment and comparison of their performance is difficult without an accurate mobility model. The performance of location management schemes depends considerably on subscriber mobility patterns. Some of the recent methods proposed in the literature are reviewed and selected that concentrate on the location updating and paging overhead. To analyze the performance of the selected proposals, two mobility models, namely activity-based mobility model and random mobility model, were used. From the results it is clear that the mobility model has a significant impact and the results described in various proposals using a random mobility model may not reflect the relative performance when deploying schemes in actual systems.

Rates of small‐scale species mobility in alvar limestone grassland

Abstract. Small‐scale species frequency and cumulative species frequency were studied in four plots in limestone grassland of the Veronica spicata‐Avenula pratensis association on Stora Alvaret on the Baltic island of Öland, Sweden. Species mobility was expressed as increase in cumulative species frequency in 20 subplots of 100 cm2. Observed cumulative frequencies from 1985–1989 in all four plots, and from 1985–1995 in one plot were compared with values following from two null models, a ‘minimal mobility’ model and a random mobility model. In ca. 50 % of the cases the observed cumulative frequency was not significantly different from the random expectation. However, in many such cases the mean annual frequency was either very high or very low.Three ways of calculating the mobility rate are presented though only one is used: (observed cumulative frequency ‐lowest annual frequency) / expected cumulative frequency. Values × 100 range from 0 to 100. There were slight differences between the four plots which were interpreted in terms of differences in grazing intensity and soil depth.It is stressed that the idea of the Carousel model has never been meant to suggest that all species would show random mobility, which we now quantify, but that species differ in their mobility rate and that the mean rate is much higher than generally realized.