Adaptive Quality of Service based Routing for Vehicular Ad hoc Networks with Ant Colony Optimization

Adaptive Quality of Service based Routing for Vehicular Ad hoc Networks with Ant Colony Optimization

Adaptive Quality of Service based Routing for Vehicular Ad hoc Networks with Ant Colony Optimization
Adaptive Quality of Service based Routing for Vehicular Ad hoc Networks with Ant Colony Optimization

ABSTRACT:

Developing highly efficient routing protocols forVehicular Ad hoc Networks (VANETs) is a challenging taskmainly due to the special characters of such networks: large-scalesizes, frequent link disconnections and rapid topology changes. Inthis paper, we propose an adaptive quality of service (QoS) basedrouting for VANETs called AQRV. This new routing protocol isto adaptively choose the intersections through which data packetspass to reach the destination, and the selected route should satisfywith the QoS constraints and fulfill the best QoS in terms ofthree metrics, namely connectivity probability, packet deliveryratio and delay. To achieve the above objectives, we mathematicallyformulate the routing selection issue as a constrainedoptimization problem, and propose an Ant Colony Optimization(ACO) based algorithm to solve this problem. In addition, aterminal intersection concept is presented to decrease routingexploration time and alleviate network congestion. Moreover,in order to decrease network overhead, we propose Local QoSModels (LQM) to estimate real-time and complete QoS of urbanroad segments. Simulation results validate our derived LQMmodels and show the effectiveness of AQRV.

EXISTING SYSTEM:

  • Existing system DUBHE is a reliable and low-latency routing protocol for transmitting data from source vehicles to stationary road-side infrastructures, and it is composed of three components including a delay model, a path choosing algorithm and an improved greedy broadcast algorithm.
  • IGRP is an efficient routing protocol for V2I communication, and it is based on effective road intersection selections, which are implemented in terms of network connectivity, delay, bandwidth and error rate. However, IGRP is a source-driven routing protocol, which requires a complete route and cannot cope with rapid topology changes in VANET environments.

DISADVANTAGES OF EXISTING SYSTEM:

  • The QoS of route is not accurate.
  • The routing exploration algorithms arenot effective and adaptive.
  • The routing selections are implemented by means of the incomplete or local QoS.

PROPOSED SYSTEM:

  • In this, an Adaptive QoS-based Routing for VANETs called AQRV is proposed to deal with the aforementioned problems. We firstly formulate this route selection issue as an optimization problem, and propose an ACO-based algorithm to solve this NP-complete issue. Then, based on both global and local pheromone (reflecting the QoS of routing paths and road segments, respectively), AQRV makes use of forward and backward ants to establish the optimal route via an opportunistic method rather than the blind flooding.
  • Once the route selection process is completed, source vehicles initiate data packets transmission, which is implemented through dynamic intersection selections. Note that the comprehensive real-time local QoS (namely connectivity probability, delay and packet delivery ratio) is derived by our mathematical models. In addition, a simple greedy carry-and-forward mechanism is adopted to relay packets between two adjacent intersections so as to reduce the effects of individual vehicle movements on the routing paths.
  • Thanks to dynamic routing decisions on intersections and closed cooperations of different ants and communication pairs, AQRV is capable of adaptively coping with rapid topology changes in VANET scenarios.

ADVANTAGES OF PROPOSED SYSTEM:

  • It improves routing stability.
  • It adaptively copes with topology changes.
  • It decrease network overhead.

SYSTEM ARCHITECTURE

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

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

SOFTWARE REQUIREMENTS:

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

REFERENCE:

Guangyu Li, Lila Boukhatem, and Jinsong Wu, Senior Member, IEEE, “Adaptive Quality of Service based Routing forVehicular Ad hoc Networks with Ant ColonyOptimization”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017.