A Simulation Study of Common Mobility Models for Opportunistic Networks

<p>Mobile Ad Hoc Network (MANET) consists of a group of mobile or wireless nodes that are placed randomly and dynamically that causes the continual change between nodes. A mobility model attempts to mimic the movement of real mobile nodes that change the speed and direction with time. The mobility model that accurately represents the characteristics of the mobile nodes in an ad hoc network is the key to examine whether a given protocol. The aim of this paper is to compare the performance of four different mobility models (i.e. Random Waypoint, Random Direction, Random walk, and Steady-State Random Waypoint) in MANET. These models were configured with Optimized Link State Routing (OLSR) protocol under three QoS (Quality of Service) <a title="Learn more about Metrics" href="https://www.sciencedirect.com/topics/engineering/metrics">metrics</a> such as the Packet Delivery Ratio (PDR), Throughput, End-to-End delay. The simulation results show the effectiveness of Steady-State Random Waypoint Mobility Models and encourage further investigations to extend it in order to guarantee other QoS requirements.</p>

Mobile Ad Hoc Network (MANET) comprises a group of mobile or wireless nodes that are placed randomly and dynamically which causes the constant change between nodes. When considering a routing protocol to deploy in any given situation on MANET, factors such as the mobility model, mobility of nodes, the network size and packet size should be carefully considered because the routing protocols configured with the mobility model can highly affect the performance of MANET. This paper analysed the impact of two different routing protocols (i.e. Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR)) on the performance of Random WayPoint (RWP) mobility model. Three measures of performance metrics (i.e. average throughput, average delay and average traffic received) were used. In all three-performance metrics, the simulated results indicated that Random WayPoint (RWP) configured with OLSR protocol performed better than RWP configured with DSR protocol. This indicates that the choice of a routing protocol for a specific mobility model should be considered in a network design.

Mobile Ad hoc Networks (MANETs) represent complex distributed systems that do not rely on any infrastructure or centralized administration. These networks consist of wireless mobile devices which communicate with each other over the wireless channel. Because each mobile node (MN) has a limited transmission range, multi-hop communication is necessary to deliver data across the entire network. Such type of communication requires routing protocols which are capable of discovering multi-hop routes between the sending and receiving nodes. In addition, various mobility models are used to mimic the walking patterns of MNs in real-world environments. These models are generally categorized into two types, i.e., (i) entity and (ii) group-based mobility models depending upon their functionalities. In this paper, we assessed the impacts of different networking contexts on the performance of different mobility models. We selected Random Waypoint (RWP) and Gauss-Markov (GM) models from the first category and Reference Point group (RPGM) and Nomadic Community (NCMM) mobility models from the second. We performed extensive simulations using Network Simulator (NS-2). Simulation results reveal that there is a decline in cost as the speed of MNs is increased. In addition, node density differently impacted the performance of both types of models. The recommendation of this research will provide better understanding of the different mobility models in MANETs and their uses in real-world environments such as search and rescue operations, battlefield situations, tracking operations, people-centric networking and many more.

The research works on the mobile ad hoc networks (MANET) have attracted wide attentions over the past few years. In order to evaluate and verify the underlying protocols or applications, researchers run simulations to generate results. By controlling different simulation parameters, we can run our programs in diverse simulation scenarios. Mobility model of mobile nodes in MANET plays an important role in simulations but its importance is often ignored. Random waypoint (RWP) is one of the most deployed mobility models in papers. RWP has the properties that are understandable and quick to implement. Until recently, several defects in RWP is unknown. One is decaying average speed and another is border effect. Besides the problems in RWP, there is still a missing property in many mobility models. Diverse average speed (DAS) is a more realistic requirement for mobility models. Most mobility models only can generate one average speed scenario with the same speed range. It is reasonable to provide different average speed within the same speed range. We propose general ripple mobility model (GRMM) of speed-time pairing to provide a similar mobility model to RWP without the defects of RWP. GRMM also provides DAS to generate different mobility scenarios. The simulation results show that GRMM of speed-time pairing can generate the mobility pattern of uniform spatial distribution and diverse average speed.

Mobility models are used to evaluate the network protocols of the ad hoc network using the simulation. The random waypoint model is a model for mobility that is usually used for the performance evaluation of ad-hoc mobile networks. Mobile nodes have dynamic mobility in the ad hoc network, so the mobility model plays an important role to evaluate the protocol performance. In this article, we developed modify random waypoint mobility (MRWM) model based on a random waypoint for the mobile ad hoc network. In this article, the comparative analysis of modifying random waypoint mobility and random waypoint model on the ad hoc On-Demand Distance Vector (AODV) routing protocol has been done for a large wireless ad hoc network (100 nodes) with the random mobile environment for the 1800s simulation time. To enhance the confidence in the protocol widespread simulations were accomplished under heavy traffic (i.e. 80 nodes) conditions. The proposed model protocol has been investigated with the performance metrics: throughput; packet delivery ratio; packet dropping ratio; the end-to-end delay and normalized routing overhead. The obtained results revealed that the proposed modified random waypoint mobility model reduces the mobility as compared to the random waypoint mobility model and it is trace is more realistic.

In this paper, we revisit two classes of mobility models which are widely used to represent users' mobility in wireless networks: random waypoint (RWP) and random direction (RD). For both models, we obtain systems of partial differential equations which describe the evolution of the users' distribution. For the RD model, we show how the equations can be solved analytically both in the stationary and transient regime, adopting standard mathematical techniques. Our main contributions are 1) simple expressions which relate the transient duration to the model parameters and 2) the definition of a generalized random direction model whose stationary distribution of mobiles in the physical space corresponds to an assigned distribution.

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.

The stochastic model assumed to govern the mobility of nodes in a mobile ad hoc network has a significant impact on the network's coverage, maximum throughput, and achievable throughput-delay tradeoffs. In this paper, we compare several mobility models, including the random walk, random waypoint and Manhattan models, on the basis of the number of states visited in a fixed time, the time to visit every state in a region, and the effect of the number of wandering nodes on the time to first entrance to a set of states. We also consider mobility models based on correlated random walks, which can account for time dependency, geographical restrictions, and nonzero drift. We demonstrate that these models are analytically tractable by using a matrix analytic approach to derive new, closed-form results in both the time- and transform-domains for the probability that a node is at any location at any time for both semi-infinite and finite one-dimensional lattices. We also derive first entrance time distributions for these walks. We find that a correlated random walk (i) covers more ground in a given amount of time and takes a smaller amount of time to cover an area completely than a random walk with the same average transition rate; (ii) has a smaller first entrance time to small sets of states than the random waypoint and random walk models and (iii) leads to uniform distribution of nodes (except at the boundaries) in steady state.

NS-3 has been one of the popular network simulator software for many years especially in research related to Mobile Adhoc Networks (MANETs). In NS-3, there is provision of several mobility models including Random Waypoint (RWP) mobility model and Steady State Random Waypoint (SSRWP) mobility model. RWP mobility model suffers from the transition phase related imperfection. SSRWP mobility model overcomes this limitation of RWP mobility by allowing the steady state initialization states of nodes in terms of position, speed and pause time of mobile nodes right from the beginning of the simulation. As SSRWP mobility model avoids any requirement of warm-up (cut-off) phase of RWP mobility model, it saves a significant amount of time of warm-up (cut-off) phase as well as establishes a high level of confidence in results obtained due to absence of any subjective guess. In the present work, RWP and SSRWP mobility models have been investigated using AODV routing protocol and it has been found that a way to mitigate the misleading effect of the transition phase of RWP mobility model is to have a sufficiently large simulation time which results, to a good extent, in convergence of performance of RWP mobility model toward that of SSRWP mobility model.

A pioneering body of work in the area of mobile opportunistic networks has shown that characterizing aggregated inter-contact time between mobile nodes is crucial. The most common approaches to study aggregated inter-contact time (ICT) in literatures are focused on a certain type of mobile wireless networks. Up to now, it still lacks a general approach to model the aggregated ICT effectively in different type of networks. This paper proposes a new approach to model aggregated ICT based on extreme value theory (EVT), which uses the generalized Pareto distribution as the unique asymptotic model of the tail distribution. Mean excess function is proposed to choose the threshold value and also other parameter estimation methods to the statistical model are discussed and applied to real mobility traces collected from different opportunistic networks, such as social pocket switched networks and vehicular ad hoc network. A decision rule based on confidence level of parameter is proposed to determine the statistical characteristics of aggregated ICT. By performing extensive experiments using EVT-based model, the aggregated ICT distributions for different type of networks are obtained. To show how well the EVT-based model actually fits the data in the tails, the complementary cumulative distribution function in a logarithmic scale is used to validate the model. Also according to the Kolmogorov---Smirnov test, it illustrates that EVT-based distributions with different parameter values fit the tails well at the desired significance level 0.05 for the taxi mobility in VANET and the human node in the other type of opportunistic networks. Finally, some prospective applications based on the statistical model are discussed in designing new network protocols.

In this paper, we study information propagation in a 2D mobile ad-hoc network, where mobile nodes are randomly and independently distributed on a torus following a homogeneous Poisson process with a given density. Nodes in the network move following a random direction mobility model. A piece of information is broadcast from a source node to all other nodes in the network, using a Susceptible-Infectious-Recovered (SIR) epidemic routing protocol. A distinguishing feature of the SIR algorithm, which leverages the mobility of mobile users, is that a relay node carries and forwards a piece of information for a specified amount of time. We first propose a metric fundamentally characterizing the information propagation in mobile ad-hoc networks. Then analytical results are derived for the probability that a non-zero fraction of nodes receive the information in the limit of large network size and for the expected fraction of nodes that receive the information. The analytical results are verified using simulations. The research provides useful insights on the design of mobile ad-hoc networks.

An Opportunistic Network is an extreme network where the communication mainly depends on the mobility of the participating nodes to address the intermittent connectivity. This opportunistic routing utilizes a store-carry-forward paradigm exploiting node mobility and local forwarding to transfer the messages. The mobile nodes are normally low-power portable wireless communication devices employing as wireless ad hoc network for multi-hop transmission. With the limited resource, the performance of the routing protocols can be degraded. Thus, it is vital to consider the energy consumption of the mobile node in this opportunistic environment, especially with different mobility patterns. This paper aims to study and analyze the energy usage on the node mobility. The results from the simulations show that MapBased mobility models consume more energy than random based mobility models while gaining higher delivery ratio. In the random based models, random direction consume more power than random waypoint and random walk respectively.

Mobile ad hoc networks (MANETs) will play a vital role in civilian and military applications where users move around and share information with each other. The movement of users varies depending on the environment, e.g. people may move randomly in different directions (Random Waypoint and Gauss Markov mobility models); or walk, run and drive in two directions in the street (Manhattan Mobility Model); or move as a group (Reference Point Group Mobility model). The interaction between mobility patterns and routing protocols contributes significantly to vary the overall network performance. We build an analytical framework that shows an analysis structure for the overall network performance test. In this framework, we first compare the properties of the mobility models that are designated for MANETs. Second, we measure single path (proactive and reactive) and multipath (proactive and reactive) routing protocols across the mobility models by tuning into TCP and CBR traffic individually. Finally, we examine the performance of each routing protocol across mobility models and discuss the possibility of interaction between them. Most of the previous findings only evaluate the impact of mobility models and single path routing protocols with CBR traffic, whereas a significant finding of this study is that how the interaction between mobility models and single path and multipath routing protocols varies depending on the usage of traffic (TCP and CBR).

Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. Despite the importance of type of the exchanged data between the knots on the QoS of the MANETs, the mul-tiservice data were not treated by the larger number of previous researches. In this paper we propose an adaptive method which gives the best performances in terms of delay and throughput. We have studied the impact, respectively, of mobility models and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio) of routing protocol (On-Demand Distance Vector) AODV by using in the first a multiservice VBR (MPEG-4) and secondly the Constant Bit Rate (CBR) traffic. Finally we com-pare the performance on both cases. Experimentally, we considered the three mobility models as follows Random Waypoint, Random Direction and Mobgen Steady-State. The experimental results illustrate that the behavior of AODV change according to the model and the used traffics.

Opportunistic Networks Model with Restricted Time-Space