Journal of Mobile Multimedia, © Rinton Press
ROUTING OPTIMIZATION FOR VANET COMMUNICATION My Driss LAANAOUI University CADI AYYAD
[email protected] Said RAGHAY University CADI AYYAD
[email protected] Received (to be filled by the JMM editorial) Revised (to be filled by the JMM editorial)
Numerous efforts are currently under progress to enhance the safety and efficiency of vehicular traffic through intelligent transportation systems. In addition, the growing demand for access to data and information from human users on the go has created the need for advanced vehicle-to-vehicle and vehicle to roadside communication systems capable of high data rates and amenable to high degrees of node mobility. The importance of inter-vehicle communication is increasing due to its role in organizing road. In this paper we present our proposition witch consisting of a new routing protocol VANET (vehicle AdHoc Network). This protocol is based on the localization of the node, and also the score assigned to each vehicle and the cost for each junction. We evaluate the performance of our protocol IRUV by comparing it with the VANET protocols: LAR and GyTAR in terms of: End to End Delay, and Delivery Ratio. To demonstrate the performance of our proposal, we used a traffic simulator VanetMobiSim to generate a realistic traffic. The trace of this traffic will be integrated into the simulation of the proposed protocol using the network simulator NS2.
Key words: VANET, routing, simulation, Dijkstra, urban environment, Delivery Ratio, end to end delay, IDM.
1. Introduction Today, many research works are interested in Ad Hoc wireless networks due to their low cost when there is a need to communicate in the absence of infrastructure. To improve road safety or allow Internet access for passengers, road safety systems have been emerged to ensure exchange intervehicle and fixed vehicle-infrastructure information in a wireless network. The behavior of active security systems is reactive, because it is based on a real-time feedback, like the weather information and de-icing systems bridges which use autonomous sensors for collecting data with high positioning precision and integrate wireless technologies. Driving and cooperative applications are integrated into vehicles to introduce anticipatory behavior in vehicular security systems. This kind of systems is designed to prevent road accidents by developing a security assistant to help drivers in avoiding risk driving situations. In addition, the inter-vehicle communication doesn’t provide only safety for drivers and driving environment, but also it improves mobility, comfort and reduced environmental impact. Hence, vehicle must be equipped with a geographic localization system, a dynamic traffic map and a set of sensors to communicate their positions, speeds and other
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information. This information will be used by cooperative security applications which suffer from the following problems: The dissemination of the message between vehicles or between vehicle and infrastructure entails latency time. Since the critical reaction time of a security system must be of a few milliseconds, the information available is much less useful. High mobility entails a change of the path, which leads to transmission errors and limits the operation of security applications. All communication must be authentic. The lack of security reduces the reliability of the system. Several protocols have been proposed to address these issues; we studied the limitations of the latter to propose an improvement. 2. Routing protocols for VANETs The concept of routing is the mechanism which allows a node to send a packet to the destination. It is the way in which a source node selects the intermediate nodes to reach the destination. Dissemination of information consists of transporting information from a source to one or more destinations, by ensuring a reduced time for routing, reliability and better use of resources. To provide routing in VANETs, each vehicle behaves as a relay, in such a way to route the packet to the destination. In a vehicular network, each vehicle acts as a relay, ie it can be transmitter, receiver or router. Routing protocols for VANET can be classified as shown in the following figure. The first family of protocols is the flat routing which can be divided into two subsets: proactive protocols whose route is available immediately, and reactive protocols whose route is searched in the application. The second family of routing protocols provides routing in large-scale networks which are called geographical or hierarchical routing: hierarchical routing breaks the network into several clusters in order to optimize dissemination. Geographic routing is based on the geographical location routing, such as routing protocol LAR (Location Aided Routing) [Ko98].
Figure 1: VANET unicast routing protocol [11]
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3. Routing techniques 3.1 Description of routing techniques Ad hoc unicast routing schemes can be divided on two categories: First category is topology base, this use a proactive or reactive approach to create routes. Second category is based on the position, it use not routing tables to store route. Instead, they use position information about neighboring and destination to identify the next node forwarding to destination. The routing protocols can also be defined as flat routing or hierarchical routing. In the first one, each node has the same responsibility in the routing process. But this technique suffers from scalability issues but still is the most popular ad hoc routing techniques. The second technique is only assigned to a certain number of nodes that provide required routing information to the rest of the nodes. Recently, some routing protocols for VANETs have been proposed, In the following, we discuss GyTAR and LAR protocols. GyTAR [1] (Improved Greedy Traffic Aware Routing protocol) is an intersection-based geographical routing protocol capable to find robust routes within city environments. It consists of two modules: (i) Selection of the junctions through which a packet must pass to reach its destination, and (ii) an improved greedy forwarding mechanism between two junctions. Hence, using GyTAR, a packet moved successively closer towards the destination along streets where there are enough vehicles to provide connectivity. GyTAR out performed previous routing protocols in terms of packet delivery ratio, routing overhead and end-to-end delay. LAR [2] is an on-demand source routing protocol. LAR sends location information in all packets to (hopefully) decrease the overhead of a future route discovery. LAR uses location information for MNs to flood a route request packet for D in a forwarding zone instead of in the entire ad hoc network. This forwarding zone is defined by location information on D. 3.2 Vehicle to vehicle communication We are interested to the Vehicle to vehicle communication. One way to propagate information between vehicles very fast is to use flooding. In a naive implementation every node that receives this information will simply rebroadcast it. To avoid infinite packet duplication, each node will broadcast a given packet at most once. In addition a time to live (TTL) counter may be used to limit the area where the packet is distributed. This naive approach will transmit a large amount of redundant packets, potentially leading to severe congestion. This is known as the ‘broadcast storm problem’ [3]. Many approaches have been proposed to deal with this problem. 4. Routing performance requirements In Ad-hoc vehicle-to-vehicle communication, where no supporting infrastructure is required, vehicles communicate when they are within the radio range of each other, or when multiple hop relay via other vehicles are available. Messages need to be routed from the source to one or several destinations. Desirable characteristics of routing protocols include [5] : • Minimal control overhead • Loop-free routing paths • Low complexity • Multicast capabilities Beside the above requirements, the vehicular environment poses new challenging requirements to vehicle-to-vehicle routing protocol design, including [6]: • Adapting routing information in highly mobile topologies • Short convergence time of the routing algorithms
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Routing optimization for Vanet communication
• Short delay for neighbor discovery • Scalability In this work, we present a new geographic routing protocol VANET called “Intelligent Routing protocol in Urban environment for Vanet “(IRUV). To evaluate the performances of this protocol, we compare it with GyTAR and LAR in terms of: End to End Delay, Delivery Ratio and efficacy. GyTAR and LAR are efficient in comparison with GSR [4]. 5. Description of our approach 5.1 Description of the IRUV protocol We begin at first by description of the V2V communication with the diagram figure 2: • A vehicular system is composed of one or more area. • An area consists of several junctions and cells. • A junction may be source or candidate. • A vehicle can be elected and belongs to one or more cells class Domain Model
Système véhiculaire
Tronçon *
- Id_Tronçon: int - Distance_T: float
Vehicule -
*
Id_véhicule: int position_X: float position_Y: float * Direction: int Vitesse: float
Jonction - Id_joncton: int - Centre_J: int
Paquet Hello
+ Consulter()
- Id_Paquet hello: int - Bp: float - Pn: float
Véhicule élu
+ Calculer_N() + Determiner_Pn() + Marquer_Dist()
- Id_véhicule élu: int + Ajouter()
Cellule - Id_cellule: int - Centre_Ce: int
Appartient *
*
1..*
Paquet CDP
Envoie
1
- Id_paquet CDP: int - Centre_X: float - Centre_Y: float + Calculer_Nbr() + Deterrminer_C()
Figure 2: UML class diagram for the vehicular system
The IRUV protocol uses Multipoint Relays (elected vehicle) in each zone. The elected vehicle sends information to the neighbor’s vehicles and updates the aggregation packet where only the links that lead to the elected vehicle are authorized to enriching aggregation packet [6]. The frequency of control packets increased with mobility. IRUV adopts Dijkstra's algorithm to choice the optimal way for destination. So, we calculate the cost of junction instead of the score in GyTAR The approach adopted by IRUV protocol is given in three parts: • Collecting information on traffic segment "between source and candidate junctions".
M.D.Laanaoui and S.Raghay 5
•
Calculating the score for the candidate junction which represents the cost of the section of road. • Apply Dijkstra's algorithm to choose the best path to the destination The UML sequence diagram below describes the purpose of electing vehicle to vehicle V2V communication that can enrich the aggregation package. sd Domain Model Vehicule 1
Véhicule n
Déterminer() :Position_x, Position_y,centre_c
Déterminer() :position_xn,position_yn,centre_c
Envoie_hello1_(idp1, dist1, pn1, nbrv1)
alt
[distn-centre_c
