EXAMINING THE MOVEMENTS OF MOBILE NODES IN THE REAL WORLD TO PRODUCE ACCURATE MOBILITY MODELS

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Tanweer Alam. et. al. / International Journal of Engineering Science and Technology Vol. 2(9), 2010, 4647-4650

EXAMINING THE MOVEMENTS OF

MOBILE NODES IN THE REAL WORLD

TO PRODUCE ACCURATE MOBILITY

MODELS

TANWEER ALAM

PhD Scholar, Department of Computer Sc & Engg, Singhania University Pacheri Bari, Jhunjhnu (Rajasthan) India

DR. B.K. SHARMA

PhD Guide, Senior Scientist, NITRA, Ghaziabad, Uttar Pradesh India

Abstract :

All communication occurs through a wireless median in an ad hoc network. Ad hoc networks are dynamically created and maintained by the individual nodes comprising the network. Random Waypoint Mobility Model is a model that includes pause times between changes in destination and speed. 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 realistic, generic and comprehensive mobility models. In this paper, we examine the movements of entities in the real world and present the production of mobility model in an ad hoc network.

Keywords: Mobile Ad Hoc Networks; Mobility Models; Simulation Environment; Entities; Real World Environment; Mobile Nodes.

1. Introduction

Mobility has become a new dimension of complexity in the design of application for wireless sensor network. Mobile Computing is a technology that allows transmission of data, via a computer, without having to be connected to a fixed physical link. Mobile voice communication is widely established throughout the world and has had a very rapid increase in the number of subscribers to the various cellular networks over the last few years. An extension of this technology is the ability to send and receive data across these cellular networks. This is the principle of mobile computing. Mobile data communication has become a very important and rapidly evolving technology as it allows users to transmit data from remote locations to other remote or fixed locations. This proves to be the solution to the biggest problem of business people on the move - mobility.

2. Mobility

Mobility is the most frequent activity of the mobile host. When MH is moving from one cell to another cell in wireless network, the connection will need to be changed because one MSS can only support mobile host with its limited area. This causes frequent need of reconfiguration network topology and protocols. The more mobility, the more time spends on reestablishing communication between MH and MSS. Because the activity of MH needs support from its MSS, therefore, location management is another problem caused by the mobility of MH. Mobile hosts need to track MSS in order to obtain data from the FH or other MH. In other words, MSS also needs to keep track on MH in order to transmit the result from the FH or to update the state of current mobile host profile. Mobility of MH raises the question on location dependent data. The same query will have different results depending on the location of MH. For example, bus time table will depend on the location of bus stop.

3. Portability

The availability of mobile devices depends on their power supply. The mobile phone can live up to five days but the laptop can only be for several hours. The more complicated application requires more processing power. Redefining computation into smaller partition (fined grain) or shifting heavy process from MH to FH for processing can save

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energy. Communication in mobile hosts requires a lot of power. Compressing data or data distilling before transmission can reduce communication time. Portability of mobile devices requires more sophisticated software application. MH has smaller user interface like display screen, keyboard. Many PDA support handwriting, therefore handwriting recognition software is required.

4. Heterogeneity

One MSS needs to support broad type of mobile devices which operate in its cell, identifying what kind of hardware of the MH is important. Different MH requires different applications. When MH requests communication with other MH, the heterogeneous problems need to be taken into account. Different MSS are in different heterogeneous network and these MSS need to co-operate and communicate with each other for exchanging data. A standard interface is needed between MSS. Java technologies or a middleware like COBRA can be used to solve the heterogeneous problems.

5. Purpose of Mobility Models

Mobility models represent the movement of mobile users, and how their location, acceleration and velocity change over time. Such models are frequently used for simulation purposes when new communication techniques are investigated. Mobility management schemes for mobile communication systems make use of mobility models for future user positions.

The purpose of mobility models is to describe typical terminal movement so that the analysis for these purposes can be made. Thus, the movement pattern of users plays an important role in performance analysis of mobile and wireless networks, especially in third-generation mobile communications. One frequently used mobility model in Mobile Ad hoc Network (MANET) simulations is the Random Waypoint model, in which nodes move independently to a randomly chosen destination with a randomly selected velocity. The simplicity of Random Waypoint model may have been one reason for its widespread use in simulations. However, MANETs may be used in different applications where complex mobility patterns exist. Hence, recent research has started to focus on the alternative mobility models with different mobility characteristics. In these models, the movement of a node is more or less restricted by its history, or other nodes in the neighborhood or the environment.

6. Movements of Entities

Each node moves from its current location to a new location by randomly choosing an arbitrary direction and speed from a given range. Such a move is performed for either a constant time or a constant distance traveled. Then a new speed and direction are chosen. At the boundaries, nodes bounce off like billiard balls on a pool table. The random walk mobility model is described as a memory less mobility pattern, because it retains no knowledge concerning its past locations and speed values.

Fig. 1: Location Prediction

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In a random walk (shown in Fig.2), each node chooses a random direction (uniformly distributed in [0, 2π]) and a random speed (also uniformly distributed in [vmin, vmax]. it then moves for a time period (or over a fixed distance) with this speed, then it repeats its choice. This model is often referred to as Brownian motion, as it resembles the movement of particles suspended in a fluid.

Fig.2: The movement of three nodes with an RWM mobility model

In an equivalent view of this model, the world is divided into cells (e.g., squares) and at each step a node can jump into any of the neighboring cells (up to several steps away).

Fig.3: Random Walk Movement Pattern

When the nodes reach the edges of the bounding rectangle, they can bounce from the edges by assuming that the world is a torus. The movement can also take place on a sphere. Similar to the RWP, RWM is highly unrealistic for most scenarios. Furthermore, in the long term, the nodes tend to stay close to their origin; thus the overall mobility is limited. Also, when bounded, RWM has the same exponential inter-meeting times as RWP.

7. Generating Random Mobility Model

For generating random mobility pattern, there is no fixed direction of the nodes. Here the nodes after every pause pick up a random direction, in a truly random scenario the speed of the nodes would be a random variable, but for our simulations the speed is constant through the duration of simulation. The pseudo code for generating this type of mobility pattern is similar to the pseudo code for semi-deterministic model shown in fig. 4, except that the, new_direction() function here returns a random value ranging from 0o – 360o. A possible random model is shown in fig. 4.

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Fig. 4: Possible Random Model

For generating deterministic mobility patterns, the nodes are imparted a particular speed with which they travel but they move only in vertical or horizontal directions. When a node hits the boundary of the layout, it retraces its path with the same speed. To implement this mobility model, we fed the scenario generator module of NS with location co-ordinates as well as the turns which the node would take, resembling an urban traffic model, where the paths and speeds are predefined. A possible deterministic model is shown in fig. 5.

Fig. 5: Possible Deterministic Model

Conclusion

Mobile Ad-hoc networks have recently attracted a lot of attention in the research community as well as in industry. The mobility model is one of the most important factors in the performance evaluation of a mobile ad hoc network. Mobility is the most frequent activity of the mobile host. 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 realistic, generic and comprehensive mobility models. When Mobile Node is moving from one cell to another cell in wireless network, the connection will need to be changed because one MSS can only support mobile host with its limited area.

References

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