رئوس مطالب
- چکیده
- کلید واژه ها
- 1. مقدمه
- 2. پیش زمینه
- 3. مدل تحرک موانع (OM)
- A. ساخت موانع
- B. آرایش Voronoi و مسیرها
- C. حرکت نیمه قطعی گره
- D. تغییرات تحرک
- E. مدل انتشار سیگنال
- IV. شبیه سازی
- A. شبیه سازی محیط
- 5. نتایج
- 6. نتیجه گیری
Abstract
Simulation environments are an important tool for the evaluation of new concepts in networking. The study of mobile ad hoc networks depends on understanding protocols from simulations, before these protocols are implemented in 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 realistic, generic and comprehensive mobility, and signal propagation models. In this paper, we propose the design of a mobility and signal propagation model that can be used in simulations to produce realistic network scenarios. Our model allows the placement of obstacles that restrict movement and signal propagation. Movement paths are constructed as Voronoi tessellations with the corner points of these obstacles as Voronoi sites. Our mobility model also introduces a signal propagation model that emulates properties of fading in the presence of obstacles. As a result, we have developed a complete environment in which network protocols can be studied on the basis of numerous performance metrics. Through simulation, we show that the proposed mobility model has a significant impact on network performance, especially when compared with other mobility models. In addition, we also observe that the performance of ad hoc network protocols is effected when different mobility scenarios are utilized.
Conclusions
This paper describes an obstacle mobility model that enables the inclusion of obstacles in ad hoc network simulations that are used both to define the movement pathways of the mobile nodes by Voronoi graph tessellations, and to obstruct the transmission of the nodes. The signal propagation model determines the reduction of signal power that takes place when communicating pairs of nodes must transmit through obstacles.
Our simulation results concur with a previous mobility model comparison [8] in that the mobility model significantly impacts the performance of ad hoc network routing protocols. Through the use of the AODV protocol, we have shown that the mobility model effects a variety of performance characteristics. We have shown that realistic movement patterns effects mobility metrics such as internode connectivity, node density, and the average link duration between nodes.
There are a number of ways to further extend this work. The first of these relates to the combination of movement characteristics of various mobility models presented in Section II to create a more diverse and comprehensive mobility model. For instance, multiple people may move to a destination as a group. This movement variation allows the combination of our obstacle mobility model and the group mobility model [18]. In another scenario, people may follow well-defined pathways to travel to their destination, such as a conference hall. Once they arrive at the hall, these people follow random movement. This scenario involves the combination of the obstacle mobility model to define pathway movement and the random mobility model after a node reaches its destination.
The specific values obtained in our simulations are strongly dependent on the configuration of the obstacles in the network terrain. However, the data leads to an important conclusion. The results show that a wide range of scenarios must be studied to discern the overall performance of the routing protocol.