A Medium-Term Disruption Tolerant SDN for Wireless TCP/IP Networks

The group mobility models that can be created from the individual mobility models are discussed. The random waypoint group mobility model, the random direction group mobility model, the Manhattan group mobility model, and the sequential group mobility model which combine the RWP mobility model with the concept of the group are described. The simulation results for the RWG, RDG, MHG, and SQG are explained.

The random trip and cluster mobility model are considered as the steady-state generic mobility model. Both mobility models are described proving the fact that it is a stable (that is, perfect simulation) model. The random waypoint and other mobility models that are subsets of the random trip model are explained. The strong stochastic property of the random trip model that has the random waypoint mobility pattern is also illuminated. The scale-free property of the cluster mobility model is described in the context of the scale-free mobile ad hoc network.

The performance evaluation of ad hoc network components through simulation allows for isolation of parameters, easy access to global quantities and a statistically significant number of repeatable trials. In designing network protocols, it is important to investigate the relationship between global network performance and the underlying locally observed network characteristics. Mobility models are used to define the movement of nodes in the simulation space. A wide variety of mobility models exist, and the choice of mobility model has significant influence over locally observed metrics. Unfortunately, many mobility models exhibit spatial and temporal non-stationarity of important metrics, such that global averages of certain metrics are not representative of local observations. This finding impacts on the development of adaptive ad hoc architectures. This paper explores the spatial stationarity of frequently used mobility models. It focuses on the importance of stationarity in relation to the evaluation of performance studies. The spatial non-stationarity of link statistics, and the impact of this artefact on network performance evaluation is examined for the Toroidal Random Waypoint and Random Direction mobility models. We show that the Toroidal Random Waypoint model exhibits spatial stationarity of link statistics. Furthermore, we demonstrate that network performance studies in spatially stationary environments produce dissimilar results to those produced by non-stationary environments. This shows the importance of spatial stationarity when investigating global network performance and locally observed network characteristics.

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.

Statistical Equivalent Models, or SEMs, have recently been proposed as a general approach to study computer simulators. By fitting a statistical model to the simulator's output, SEMs provide an efficient way to quickly explore the simulator's result. In this paper, we develop a SEM for random waypoint mobility, one of the most widely used mobility models employed by network simulators in the evaluation of communication protocols for wireless multi-hop ad hoc networks (MANETs). We chose the random waypoint mobility model as a case study of SEMs due to recent results pointing out some serious drawbacks of the model (e.g., [1]). In particular, these studies show that, under the random waypoint mobility regime, average node speed tends to zero in steady state. They also show that average node speed varies considerably from the expected average value for the time scales under consideration in most simulation analysis. In order to investigate further the behavior of the random waypoint model, we developed a SEM that captured speed decay over time under random waypoint mobility using maximum speed and terrain size as input parameters. A Bayesian approach to model fitting was employed to capture the uncertainty due to unknown parameters of the statistical model. The SEM is given by the posterior predictive distributions of the average node speed as a function of time. A direct result from our model is that, by characterizing average node speed as a function of time, our approach provides an accurate estimate of the “warm-up” period required by simulations using the random waypoint mobility model. Simulation data from the “warmup” period can then be discarded to obtain accurate protocol performance results. Given that random waypoint mobility is still, by far, the most widely used mobility model in the evaluation of MANETs, the contribution of this work is potentially significant as it allows network protocol designers to continue to use the original random waypoint mobility model and yet obtain accurate results characterizing MANET protocol performance.

In present study, researcher has investigated the impact of node mobility by evaluating the performances of different routing protocols using mobility models. Detailed simulations were carried out, using QualNet simulator with varying node density. In the simulation study the Random Waypoint, Group and File mobility models were considered. Simulation results illustrated that, the performance of routing protocols significantly affect with the mobility models. Overall, the performance of various routing protocols is highly affected under the Random Waypoint mobility model than that of File and Group mobility models. It has happened because of frequent node movement under the Random Waypoint mobility model than that of other mobility models.

Problem statement: In sensor networks, some routing protocols performance differs under different mobility models. In ns2, there are two kinds of directed diffusion protocols, rate based gradient mechanism (diffusion/rate) and probability based gradient mechanism (diffusion/prob). In this research, we proposed a method to improve the performance of Directed diffusion/prob protocol by adding a new interest message propagation mechanism and analyzed the protocol under different mobility models. Approach: In this study, we describe a method for increasing the performance of diffusion/prob protocol and reduce the overhead with varying node speed and under different mobility models. We carried out the work using network simulator (ns2) and observed the performance improvement. Results: The performance of the proposed protocol is evaluated in terms of power consumption, overhead and routing load with Random way point, Random point group and Manhattan mobility models. Moreover, it is been compared with the normal diffusion/prob protocol. Conclusion: We have successfully implemented the proposed diffusion/prob protocol and compared it with other diffusion protocols with different metrics. We hereby conclude that it will be suitable for mobile scenario and the performance of the protocols are varied on different mobility models.

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.

The wireless mesh network (WMN) is an emerging and cost-effective alternative paradigm for the next generation wireless networks in many diverse applications. In the performance evaluation of routing protocol for the WMN, it is essential that it should be evaluated under realistic conditions. The usefulness of specific mobility protocol can be determined by selection of mobility model. This paper introduces a coloured Petri nets (CP-nets) based formal model for implementation, simulation, and analysis of most widely used random waypoint (RWP) mobility model for WMNs. The formal semantics of hierarchical timed CP-nets allow us to investigate the terminating behavior of the transitions using state space analysis techniques. The proposed implementation improves the RWP mobility model by removing the “border effect” and resolves the “speed decay” problem.

In MANET-DTN, the main idea is to detect the social relations between nodes in mobility models because the wireless mobile devices are carried by humans and the network uses the social relations to transport messages between isolated islands of the mobile terminals in order to increase the network performance. Today there are a lot of social and non-social mobility models. The problem is how to use these models in MANET-DTN. Therefore, proper evaluation method is needed, that is able to reveal the social aspect of investigated mobility model. Since there are a lot of methods that do not directly exhibit the social aspect of mobility models, in this paper the new evaluation method was proposed based on Louvain method for community detection and the other network graph parameter (average weighted degree). Simulations of evaluation method were made as a comparison between two random mobility models and one social based mobility model in order to point out differences between social and non-social mobility models. All models were evaluated by proposed method and other existing protocol dependent and independent methods. The main idea of the simulations was to analyse how the mobility models with social and non-social mobility models can affect the network performance and provide new and reliable tool, which enables analysis of the mobility models from social behaviour point of view.

A mobile ad-hoc network (MANET) is basically called as a network without any central administration or fixed infrastructure. It consists of a number of mobile nodes that use to send data packets through a wireless medium. There is always a need of a good routing protocol in order to establish the connection between mobile nodes since they possess the property of dynamic changing topology. Further, in all the existing routing protocols, mobility of a node has always been one of the important characteristics in determining the overall performance of the ad hoc network. Thus, it is essential to know about various mobility models and their effect on the routing protocols. In this paper, we have made an attempt to compare different mobility models and provide an overview of their current research status. The main focus is on Random Mobility Models and Group Mobility Models. Firstly, we present a survey of the characteristics, drawbacks and research challenges of mobility modeling. At the last we present simulation results that illustrate the importance of choosing a mobility model in the simulation of an ad hoc network protocol. Also, we illustrate how the performance results of an ad hoc network protocol drastically change as a result of changing the mobility model simulated.

This paper discusses the role of three mobility models namely, fully coordinated mobility, fully random mobility and emergent mobility models in improving area coverage and detection effectiveness of a set of mobile sensors in a mobile surveillance system. A novel anti-flocking algorithm that mimics solitary animal's social behavior is described. A multiagent-based system has been implemented to examine the efficiency of the different mobility model. The simulation results show that anti-flocking mobility model outperforms the fully random mobility model. This novel model provides additional features such as scalability, robustness and adaptivity comparing with fully coordinated mobility model.

A scheme for enhancing sensor network lifetime is proposed using multiple mobile CHs. The CHs controllably move toward the energy-rich sensors maintaining remaining energy more evenly, eliminating multihop transmission. Collaboration among CHs is considered to maintain their continuous connectivity to the base station (BS) to reduce the delay in communication. Network lifetime is increased by 75% by making CHs always move towards a stable equilibrium point whereas connectivity algorithm provides 40% improvement in transmission delays over existing schemes.

Since mobile networks are not currently deployed on a large scale, research in this area is mostly by simulation. Among other simulation parameters, the mobility model plays a very important role in determining the protocol performance in MANET. Based on random direction mobility model, a high dynamic adaptive mobility network model is proposed in the paper. The algorithms and modeling are mainly studied and explained in detail. The technique keystone is that normal distribution is combined with uniform distribution and inertial feedback control is combined with kinematics, through the adaptive control on nodes speed and prediction tracking on nodes routes, an adaptive model is designed, which can be used in simulations to produce realistic and dynamic network scenarios. It is the adaptability that nodes mobile parameters can be adjusted randomly in three-dimensional space. As a whole, colony mobility can show some rules. Such random movement processes as varied speed and dwells are simulated realistically. Such problems as sharp turns and urgent stops are smoothed well. The model can be adapted to not only common dynamic scenarios, but also high dynamic scenarios. Finally, the mobility model performance is analyzed and validated based on random dynamic scenarios simulations.

We study the throughput-delay performance trade-off in large-scale wireless ad hoc networks. It has been shown that the per source-destination pair throughput can be improved from Θ(1/√n log n) to Θ(1) if nodes are allowed to move and a 2-hop relay scheme is employed. The price paid for such an improvement on throughput is large delay. Indeed, the delay scaling of the 2-hop relay scheme is Θ(n log n) under the random walk mobility model. In this paper, we employ coding techniques to improve the throughput-delay trade-off for mobile wireless networks. For the random walk mobility model, we improve the delay from Θ(n log n) to Θ(n) by employing Reed-Solomon (RS) codes. Our approach maintains the diversity gained by mobility while decreasing the delay.