A realistic mobility model with irregular obstacle constraints for mobile ad hoc networks

Mobile Ad hoc Networks (MANETs) is about mobile nodes roaming around the network area. Simulation is one of the methods for evaluating the characteristics of Ad Hoc networking protocols. Mobility model of the network simulator is very important. The mobility of the nodes directly impacts the performance of the protocols. The simulation results obtained with unrealistic movement models may not correctly reflect the true performance of the protocols. The majority of existing mobility models for ad hoc networks do not provide realistic movement scenarios; they are limited to random walk models without any obstacles hence the need to address mobility with obstacles. In this paper, we proposed a solution to realize a realistic movement models through the incorporation of obstacles by studying the Performance Evaluation of campus mobility model in Mobile Ad Hoc Networks. Therefore, the objective of our proposed Campus Mobility Model (CMM) has been designed to model the movement of mobile nodes in terrains that resemble the real world topographies. The objects model buildings and other structures that provide a barrier to both the movement of the mobile nodes, as well as the wireless transmission of these nodes. In modeling such a terrain, a user can define the positions, shapes and sizes of these objects. Finally we evaluated the Campus Mobility model based on physical characteristics and the impact on network topology and routing performance. Simulation results showed that the use of obstacles and pathways has a significant impact on the network topology and the performance of the routing protocol.

The study of mobile ad hoc networks depends on understanding protocols from simulations, before applying on a real world setting. To produce a real-world environment within which an ad hoc network can be formed among a set of nodes, there is a need for the development of a realistic, generic and comprehensive mobility model instead of random-based models. Previously, realistic mobility models such as obstacle mobility and pathway mobility model, etc, has been proposed. In these mobility models, there are movement paths and obstacles that constrain the movements and signals of the nodes. In this paper, we propose a new Obstacle Mobility Model Based On Activity Area. In this model our focus is on the movement pattern of the nodes, first we constructed environment simulation that included predefined pathways and obstacles. Then, we consider several clusters each of which has a given geographic activity area, speed and capacity. The nodes become member of clusters. In our model similar to real world, each node belongs to a particular activity area that its existence probability, in this area, is more than other places. This paper shows that various MANET environments can be modeled based on this work. A sample environment is also simulated and the result is compared with the Obstacle Mobility and Random Waypoint model. The results show that movement pattern and speed of the nodes have a significant influence on the performance of MANET protocols.

Mobility modelling plays a pivotal role in evaluating the performance of Mobile Ad Hoc Networks (MANETs), as the movement patterns of nodes strongly influence routing efficiency, connectivity, and network stability. Existing mobility models, particularly entity and group-based frameworks, have proven useful in simulating various MANET applications but remain limited in capturing the complex movement behaviour characteristic of Search-and-Rescue (SAR) operations in disaster scenarios. This study proposes a realistic hybrid mobility model that integrates the essential features of both entity and group mobility paradigms to better represent the coordinated yet flexible dynamics of SAR teams. Three sets of simulations were performed using the Network Simulator 2 (NS2). The first and second simulations focused on generating and combining existing entity and group mobility patterns using the BonnMotion tool, resulting in two composite models (Real1 and Real2). The third simulation compared these models using AODV and DSDV routing protocols under varying node mobility levels and traffic conditions. Key performance metrics, including relative mobility, node degree, partition count, link duration, packet delivery ratio (PDR), throughput, and average end-to-end delay, were analysed. Results demonstrate that it is feasible to concatenate existing mobility models into a coherent hybrid framework. Among the developed models, Real2 exhibited superior performance in most test conditions, yielding higher PDR, lower delay, and more stable connectivity than its constituent models. These findings confirm that the performance of MANETs is highly dependent on mobility realism. Consequently, selecting a model that accurately reflects the behavioural characteristics of the target scenario is essential for credible MANET performance evaluation in emergency response contexts.

The mobility model is one of the most important factors in the performance evaluations of a mobile ad hoc network (MANET). The Manhattan mobility model has been used to model the node's mobility, where the movement pattern of mobile node on streets and roads defined by maps. However, DakNet ad hoc network that uses wireless technology to provide digital connectivity among villages, kiosks and private communication devices and between kiosks and a hub (for non-real time internet access) using low-cost WiFi radio transceivers. One typical mobility behavior is geographical restriction movement. To investigate DakNet scenario an underlying realistic mobility model is desired. In this paper, we propose a novel mobility model “Digital Postal Mobility Model” (DPMM), which closely approximates the mobility patterns in DakNet scenario; it models the movement of nodes at pre-defined path and have a set of destinations and also visit all destination. We demonstrate our proposed mobility model by evaluating various MANET routing protocols, including DSR and DSDV, the performance of DPMM is efficient than existing geographical restricted models and NS simulation results shows that the choice of mobility model has significant impact on network performance.

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.

Wireless network refers to any characteristic of a computer network that does not depend on line connectors or physical connections. One of the outstanding characteristic of wireless Mobile Ad hoc Network (MANET) that is significantly different compared to the traditional wired networks is mobility. A user i.e. typically represented by a mobile station or nodes can freely move, whilst being connected to the network. Generally, MANET is a collection of wireless mobile nodes that possess the ability to intercommunicate with one another without any predefined infrastructure or centralized administration support [1]. They are self-organized, autonomous and decentralized multi-hop wireless system of mobile nodes [2]. As such, a reliable MANET routing protocol is needed to enable data to be propagated multi-hops. An example of such routing protocol is Ad hoc On Demand Distance Vector (AODV). Using AODV as the basis of this work, this research paper discusses the best approach to conduct simulation experiment particularly for discrete-event based simulator such as Network Simulator. The underlying principle in MANET simulation is to ensure results are as credible to the empirical experiment. Therefore, iteration of experiment is essential to determine the final result. Much research work also fails to identify the existence of transient phase in simulation work. Failure to address the issue may cause inconsistent result. In addition, a validation methodology based on comparison method is also presented. Although such technique is fairly common, it is one of the most effective method to assess the reliability of the simulation tool.

Realistic mobility models are crucial for the simulation of Delay Tolerant and Opportunistic Networks. The long standing benchmark of reproducing realistic pairwise statistics (e.g., contact and inter-contact time distributions) is today mastered by state-of-the-art models. However, mobility models should also reflect the macroscopic community structure of who meets whom. While some existing models reproduce realistic community structure - reflecting groups of nodes who work or live together - they fail in correctly capturing what happens between such communities: they are often connected by few bridging links between nodes who socialize outside of the context and location of their home communities. In a first step, we analyze the bridging behavior in mobility traces and show how it differs to that of mobility models. By analyzing the context and location of contacts, we then show that it is the social nature of bridges which makes them differ from intra-community links. Based on these insights, we propose a Hypergraph to model time-synchronized meetings of nodes from different communities as a social overlay. Applying this as an extension to two existing mobility models we show that it reproduces correct bridging behavior while keeping other features of the original models intact.

<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>

A mobile ad hoc network (MANET) consists of mobile nodes that communicate with each other without any infrastructure. MANET has various applications including military operations, rescue operations, and many other situations that require rapidly deployable communication networks. In order to evaluate the performance of such networks accurately through simulations, we need to use realistic conditions when simulating. User mobility pattern is an important factor that affects the performance of the network significantly. Recently, a number of mobility models have been proposed in order to produce realistic node mobility patterns. Mobility models differ considerably depending on the applications for which they are designed. In this paper, we present a unified mobility model framework. The framework can generate most of widely used mobility models with a short script. We show this by applying the framework to generate most of the existing mobility models. This framework expedites the performance evaluation process of MANETs since users do not need to write code from scratch to generate the application-specific moving patterns for the nodes.

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.

In the current dynamic probabilistic algorithm, the retransmission probability (pt) has always been formulated as a linear/non-linear function of a single variable, namely, the number of first-hop neighbors (k), and therefore denoted as pt(k). The performance of the probabilistic algorithm has severely suffered in the presence of noise due to the reduction in the probability of reception (pc) of route request packets by receiving nodes. This chapter presents a detailed description of a new dynamic probabilistic algorithm in which pt is determined as a function of k and pc, and therefore, it is referred to as the Dynamic Noise-Dependent Probabilistic (DNDP) algorithm. The DNDP algorithm is implemented using the Mobile Ad Hoc Network (MANET) Simulator (MANSim), which is used to simulate a number of scenarios to evaluate and compare the performance of the algorithm with pure flooding and fixed and dynamic probabilistic algorithms. The simulation’s results demonstrated that the DNDP algorithm provides an excellent performance in various network conditions, where it almost maintains the same network reach-ability in noiseless and noisy environments, with the noisy environments inflicting an insignificant increase in the number of redundant retransmissions.

Mobile Ad Hoc Network is a collection of mobile nodes forming temporary network. In MANET routing protocols are classified as Proactive, Reactive and Hybrid. The work presented here evaluates performance of three Reactive routing protocols such as AODV, DSR and TORA under six performance metrics such as packet delivery ratio, routing overhead, packet loss, normalized routing load, throughput and end to end delay The nodes follow two realistic mobility models such as Reference Point Group Mobility model (RPGM) and Manhattan Grid (MG) model. This work also presents the statistical analysis of AODV, DSR and TORA in Manhattan Grid (MG) model and Reference Point Group Mobility (RPGM) model in low load with low speed, average load with average speed, high load with high speed and very high load with high speed. Contribution in this work is beneficial in deciding which protocol to choose for better QoS.

An Overview of MANETs Simulation

Movement patterns of mobile nodes significantly affect the performance of a Mobile Ad hoc Network (MANET) routing protocol. Thus, it is essential that the mobility traces generated by a mobility model closely match the trace data collected from experiments. In addition, the probability distribution of mobile nodes (over the simulation area) varies with time before it comes to a steady-state. In other words, distribution of mobile nodes in steady-state is independent of their initial position. If traces generated by a mobility model are used before its steady-state is reached, this variability in distribution may lead to misleading results, called initialization bias. Thus, for credible MANET simulations, it is required that a mobility model used (1) is realistic (i.e., its mobility traces closely match the experimental data) and (2) starts in a steady- state (i.e., there is no initialization bias). In this work, we analyze a recently published realistic mobility model, called SLAW. The SLAW mobility model is based on real GPS traces collected from five outdoor sites. Previous work with SLAW is done by discarding the first few hours of simulation time; however, discarding initial data does not guarantee that the model has reached its steady-state. Thus, the main contribution of our work is that we provide methods for sampling from the steady- state distributions of mobile nodes' locations and pause- times. Sampling from the steady-state distributions allows the SLAW mobility model to start in a steady-state and thus, avoids initialization bias related to the mobility model.

SummaryThe advances of localization‐enabled technologies have led to huge volumes of large‐scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context‐aware advertising, city‐wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio‐temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members' distribution, and radius of gyration. We validate the CGAM synthetic traces against real‐world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding‐based and community‐based routing protocols.