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Introduction To Vanet Networks

Discussion in 'VANET Networks' started by Homaei, Nov 2, 2013.

  1. Homaei

    Homaei Administrator Staff Member

    For people living in developed countries the sheer volume of road traffic can be a daily nuisance. In addition, the road traffic conditions affect the safety of the population since 1.2 million people worldwide are estimated to be killed each year on the roads1. For this reason, nowadays the automotive industry and governments invest many resources to increase road safety and traffic efficiency, as well as to reduce the impact of transportation on the environment. The application of communications and information technologies for this purpose has opened a new range of possibilities. One of the most promising areas of research is the study of the communications among vehicles and road-side units, or more specifically the Vehicular Ad-hoc Networks (VANET) [58]. This kind of networks are self-configuring networks composed of a collection of vehicles and elements of roadside infrastructure connected with each other without requiring an underlying infrastructure, sending and receiving information and warnings about the current traffic situation (see Figure 1). Nowadays, WiFi (IEEE 802.11 based) technologies are the most commonly used for deploying VANETs. The vehicles are equipped with wireless network interfaces which use either IEEE 802.11b or IEEE 802.11g standards for access media. However, these are general purpose standards and they do not fit properly the requirements of high dynamic networks such as VANETs. Currently, DSRC (Dedicated
    Short-Range Communicatio) [108] has been proposed as the communications standard specifically for VANETs, it is a short medium range communications service that offers very low latency and high data rate. DSRC is based upon the standards IEEE 802.11p and IEEE 1609 family.


    Fig1. VANET use case: Warn of obstacle in the road.

    The use of IEEE 802.11 (not cellular) standards implies that vehicles communicate within a limited range while moving, thus exhibiting a topology that may change quickly and in unpredictable ways. In such kind of networks, previous to its deployment, it is crucial to provide the user with an optimal configuration of the communication protocols in order to increase the effective data packet exchange, as well as to reduce the transmission time and the network usage (with their implications on higher bandwidth and lower energy consumption). This is specially true in certain VANET scenarios in which buildings and distances discontinue communication channels frequently, and where the available time for connecting to vehicles could be really short.

    The efficient protocol configuration for VANETs without using automatic intelligent design tools is practically impossible because of the enormous number of possibilities (NP-problems). It is especially difficult (e.g., for a network designer) when considering multiple design issues, such as highly dynamic topologies and reduced coverage. All this motivates the use of metaheuristic techniques [15] which
    arises as well-suited tools to solve this kind of problems. Unfortunately, few related approaches can be found in the specialized literature. In Alba et al. (2006) [5], a specialized Cellular Multi-Objective Genetic Algorithm (cMOGA) was used for finding an optimal broadcasting strategy in urban Mobile Ah Hoc Networks (MANETs). Chiang et al. (2007) [33] developed an Ant Colony based model for resource management in VANETs. More recently, in Dorronsoro et al. (2008) [40], six versions of GAs (panmictic and descentralized) were evaluated and used in the design of ad hoc injection networks.

    In the present Thesis, we face the Optimal File Transfer protocol Configuration (OFTC) problem in VANETs, which deals with the optimization of VDTP (Vehicular Data Transport Protocol) [23], by means of five different state-of-theart optimization techniques (metaheuristic algorithms). This problem lies in the core of any VANET application, and thus optimal configuration is a major concern.
    Also, we face many optimization algorithms because this is a new field, and their relative advantages are still unclear. These algorithms are two swarm intelligence techniques: Particle Swarm Optimization (PSO) [70] and Differential Evolution (DE) [128]; two evolutionary algorithms: Genetic Algorithm (GA) [15] and Evolutionary Strategy (ES) [120]; and a trajectory search technique, Simulated Annealing (SA) [73]. For our tests, two typical car-to-car environment instances have been defined: urban and highway scenarioss. We rely on a flexible simulation structure using VanetMobiSim/Ns-2 [8] (realistic VANET simulator) for optimizing the transmission time, the number of lost packets, and the amount of data transferred. One additional contribution of this work is to provide the specialist with a useful
    platform, embedded within ns-2, to configure network protocols and hence obtaining a fair QoS control in VANETs.

    Referenced by: http://www.wsnlab.org
    Author: Mohammah Hossein Homaei
    Wireless Sensor Networks Laboratory of Iran
    divon and Rabiee like this.
  2. doy

    doy New Member

    hi nice introduction about VANET,,
    i working on my final project about VANET, i use ns3 for my simulation, but there is something make me doubt about DSRC implementation in simulator such as ns2 or ns3, you said DSRC based on 802.11p , and it should be there is model or standard that we can use in our simulator, i still using 802.11b standard on my simulation, and i just extend the wireless range for fixed with VANET application :p
    and one thing, its about VANET mobility, as you know its totally random, but you can predict any vehicle mobility since they are on the road,, and its make a sense about something algorithm that we can use for VANET behavior,, for a while i using SUMO for tracing vehicle mobility and i just put the car wherever i want, and also its make me doubt too,
    Homaei likes this.

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