In general, a mobile ad hoc network (MANET) is a set of wireless nodes communicating with each other in the absence of any infrastructure. Due to the availability of small, inexpensive wireless communication devices, the MANET research area has attracted much attention from academia and industry in recent years. In the near future, MANETs could potentially be used in various applications such as mobile classrooms, battlefield communications, and disaster relief. The MANET simulation has several key parameters, including the mobility model and the communicating traffic model. In this chapter, we mainly focus on the analysis, modeling of mobility models and also on the study of the impact of mobility on the performance of MANET. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay The mobility model is designed to describe the movement pattern of mobile users and how their location, speed, and acceleration change over time. Since mobility models can play an important role in determining the performance of MANET, it is desirable that mobility models reasonably emulate the motion model of targeted real-world applications. Each mobile node in a MANET is treated as an autonomous peer, and the random mobility patterns of mobile nodes should be analyzed to study the performance dependence of the variable topology network. Additionally, a MANET is a resource-constrained communications network with limited energy, computing resources, and memory. Over the years, many mobility models have been used to analyze the performance of mobile ad hoc networks. Many mobility models are designed to better recreate real-world scenarios for application to MANET. The statistical properties of these mobility models are analyzed by designing different mobility metrics and studying the influences of mobility models on the performance of network protocols, including routing, service discovery, and peer-to-peer mobile applications. Thus, when evaluating the performance of MANET, it is necessary to choose the appropriate underlying mobility model. For example, nodes in the Random Waypoint model behave very differently from nodes moving in groups. It is not appropriate to evaluate applications in which nodes tend to move together using the Random Waypoint model. There is therefore a real need to develop a deeper understanding of mobility models and their impact on MANET performance. A general method for creating realistic mobility models should be built using trace-based mobility models and provide the information to users. However, as MANETs have not been implemented and deployed on a large scale, obtaining real mobility traces becomes a major challenge. Therefore, various researchers have proposed different types of mobility models and represented them “realistically” with different style. Much current research has focused on so-called synthetic mobility models that are not trace-based. In previous studies on mobility patterns in wireless cellular networks, researchers mainly focus on the movement of users relative to a particular area (i.e., cell) at a macroscopic level, such as cell change rate, handover traffic and blocking probability..