V2V Routing in a VANET Based on the Autoregressive Integrated Moving Average Model

V2V Routing in a VANET Based on the Autoregressive Integrated Moving Average Model

ABSTRACT:

With the development of vehicle networks, the information transmission between vehicles is becoming increasingly important. Many applications, particularly regarding security, are based on communication between vehicles. These applications have strict requirements for factors such as the quality of communication between vehicles and the time delay. Many theoretical communication protocols ignore the presence of buildings or other obstacles that are present during practical use, especially in urban areas. These obstacles can cause a signal to fade or even block direct communication. Many vehicles are often parked at the roadside. Because of their location, these parked vehicles can be used as relays to effectively reduce the shadowing effect caused by obstacles and even solve communication problems. In this paper, we study the problem of parked-vehicle-assistant relay routing communication in vehicle ad hoc networks. We propose an efficient Parked Vehicle Assistant Relay Routing (PVARR) algorithm that is composed of four parts: a periodic Hello packet exchange mechanism, candidate relay list update, communication link quality evaluation and candidate relay list selection. Simulation results reveal obvious advantages for indexes such as the quality of communication, success rate, and time delay.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium Dual Core.
  • Hard Disk : 120 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 1 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : UBUNTU/Windows XP/7
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command  Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Gang Sun, Liangjun Song, Hongfang Yu, Victor Chang, Xiaojiang Du, Senior Member, IEEE, Mohsen Guizani, Fellow, IEEE, “V2V Routing in a VANET Based on the Autoregressive Integrated Moving Average Model”, IEEE Transactions on Vehicular Technology, 2019.

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