An Efficient Cross Layer Routing Protocol for Safety Message Dissemination in VANETS with Reduced Routing Cost and Delay Using IEEE 802.11p
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For successful message dissemination in urban vehicular ad hoc networks (VANETs) with reduced route cost and delay is challenging task due to high mobility of the vehicles. Existing cross-layer cooperative routing (CLCR) protocol in VANETs utilizes vast transmission power and increases route cost due to unnecessary broadcast of Hello messages in selecting relay nodes for packet routing. In this paper an enhanced CLCR (ECLCR) with IEEE 802.11p has been proposed, by introducing new mechanism: selecting appropriate relay nodes by calculating neighbor set ratio (NSR) using neighborhood knowledge to acquire more robust route for successful dissemination of packet, then adding a parameter to packet header such as mobility, which can store total network NSR for each route request packet to reduce delay. The performance of the newly proposed algorithm has been evaluated with network simulator-2.34 tool and compare with existing protocols under different conditions. Furthermore, an extensive simulation experiments have been carried out and it is observed that the proposed ECLCR using IEEE 802.11p standard outperforms over existing approaches.
KeywordsCross layer cooperative routing VANETs Relay estimation Average delay Route cost
VANET is special case of wireless mobile communication networks, where nodes are assumed as vehicles . VANETS provide communication among vehicles and combines roadside units to vehicles to provide road safety and comfort. It allows vehicles to communicate each other even out of radio coverage area for finding route. The communication among vehicles in VANET depends on the type of routing metric used, as there is no centralized infrastructure and high mobility of vehicles . As per the literature survey, different layered mechanisms have been provided for safety message broadcasting in vehicular networks with proper routing. For example, Ad hoc On Demand Multipath Distance Vector (AOMDV) protocol, is an enhancement to Ad hoc on demand Distance Vector (AODV) routing protocol, can able to identify node-disconnected and link-disjoint routes while identifying paths for successful data transmission due to circumstances of node-disjoint paths are stronger when compared to link-disjoint route, as a result the numbers of node-disjoint paths are less than that of link-disjoint paths . Where the disconnected routes are identified for message dissemination but route cost is high leads to unnecessary broadcast of Control packets.
In Ad Hoc on Demand Multipath Distance Vector with Retransmission counts metric (R-AOMDV), a cross layer design illustrated how routing is implemented with retransmission counts, in turn increased excessive use of control packets . A routing protocol provides reliable Roadside to Vehicle communications in rural areas . In this roadside unit takes care of maintaining proper routes to forward the packets on fly by predicting lifetime of links without any relay identification to reduce the delay and route cost for urban environment. Wu et al.  have proposed an efficient AODV with backbone based routing for message dissemination to increase packet delivery ratio. Still this protocol performance is limited during low vehicle density due to frequent link breaks, in turn leads to delay in message dissemination.
Another work in  focused on link quality based on total network weight along with link expiration time. However it suffers from route discovery phase which is similar to AODV, where unnecessary flooding of hello packets takes place results into high route cost. A different approach with geographic routing was followed in  to improve reliability of the route by combining AODV. In this work new field format called recent positions of destination vehicle added to RREQ packet to reduce the hop count. RREQ will reach the destination, leads to improved delay performance and increased route cost. Ledy et al.  have presented an improved AODV (V-AODV), where path discovery is done by identifying delay from node to node through send and receive times of Hello packets. V-AODV makes decision in path discovery with increased route cost due to unnecessary flooding of control packets. Despite the numerous layered protocols [3, 4, 5, 6, 7, 8, 9] designed for successful message dissemination, selects and saves least hops rather stable or robust paths to reduce the delay parameter only.
In [10, 11] authors have proposed new cross layer approach for VANETs by applying mobility model to estimate neighboring node movement to chose longest life time route. However in both the proposed methods, consideration of link quality leads to increased hops, which increases End–End delay. In [12, 13] authors have focused on total network weight along with link expiration time. But it suffers from route discovery phase which is similar to AODV [4, 14] for VANETs. The existing routing schemes from [10, 11, 12, 13] discussed above, in which relay vehicles are identified based on the process of flooding RREQ packets to all the neighbors in the transmission range at times. Thus leads to high overhead due to generation of control packets for path discovery as all the methods come under On-Demand routing protocol, such as AODV.
To address the aforementioned issues, researchers have identified cooperative routing protocols for vehicular networks [15, 16, 17]. Cooperative communication is a new physical layer technique which allows communication among multiple vehicles, targeting at improvising the overall end-to-end throughput. Towards these authors in  have proposed Cross-Layer Cooperative Routing (CLCR) mechanism to choose adaptive relay vehicles based on distance parameters in VANETs. Furthermore, CLCR extend the lifetime of routing path by identifying link life time to reduce the frequency of route rediscovery. However CLCR suffers from increased route cost and transmission power in disseminating data packets as route discovery is similar to AODV for VANETs. Furthermore in urban VANETs verbatim adoption of CLCR is still challenging issue where vehicle density and speed are intermittent.
To this end, we intend to propose an Enhanced CLCR (ECLCR) protocol by introducing new mechanism: selecting appropriate relay nodes by calculating Neighbor Set Ratio (NSR) using neighborhood knowledge to acquire more robust route for successful dissemination of packet, then adding a parameter to packet header such as mobility, which can store total network NSR for each Route Request (RREQ) packet to reduce delay. ECLCR (Enhanced CLCR) to fulfill the performance metrics such as improved Packet Delivery ratio with reduced route cost and delay over CLCR.
The paper is structured into different sections as follows. Section II summarizes the proposed work. Section III illustrates performance analysis of proposed algorithm. Finally, section IV concludes the work.
2 Proposed Mechanism
On receiving RREQ, every vehicle first checks the value of common neighboring vehicles for an appropriate vehicle to decide whether to plunge or carry on before proceeding to next process. If data id and data sequence number belongs to VIT, then insert the path traversed along with route link (rt_link). Later broadcast the data packet into neighboring vehicle with less NSR, which greatly reduces route cost. Repeat the same for every neighboring vehicle with less NSR and update the VIT.
3 Performance Analysis
Urban simulation parameters for NS-2.34 tool
2500 × 2500
Vehicle speed range (km/h)
Simulation execution time (s)
Number of vehicles
Radio transmission range (m)
Number of connections
4 Results and Discussion
Which reduces greatly the use of control packets such as RREQ and RREP packets. It is observed that the ratio of bytes transmitted control packets to that of bytes of transmitted data packets is less for different speeds in proposed method.
On whole it is evident that ECLCR protocol performance is much better than CLCR  in both cooperative and non cooperative paths in high mobility scenarios i.e. from 90 to 108 km/h. This is because of selection of relay vehicle at times based on number of neighboring vehicles to a particular relay vehicle, which establishes stable links among vehicles and further more adding overall network neighbor vehicle ratio into RREQ packet header, which leads to less delay while transmitting data packets between source to destination. Thus the proposed method is efficient in disseminating emergency messages related to accidents and traffic conditions to nearest vehicles with reduced delay.
In this work, we have presented an enhancement to existing protocols using cross-layered approach to assess most appropriate relay vehicle. The proposed protocol enhanced by adding a parameter such as mobility to the packet header, it can be stored the entire network fewest neighbors for each Route Request (RREQ) packet. With the help of simulation results it is identified that the path elected is stable and accessing speed between the vehicles and route cost has come down greatly. Furthermore, we intend to employ clustering concept into proposed cross layered mechanism based on relative speeds. In turn, control the frequent link failures in meager networks or light vehicle road segment under critical situations. This could satisfy recent advancements in Multimedia applications like live video/audio streaming among many users over wide range for vehicle to vehicle communication.
Authors are very much thankful to both the editor and referee for giving valuable critical and precise comments/suggestions to improve the quality of this manuscript. Dr. D. Venkata Ratnam would like to express his thanks to the Department of Science and Technology, New Delhi, India for funding this research through SR/FST/ESI-130/2013(C) FIST program. The work of Dr. D. Venkata Ratnam is supported through F. 301/2013(SAII)/RA201416GEANP5585. Authors would like to thank Dr. I. A. Pasha, Professor and Head of the Department, Electronics and Communication Engineering, B V Raju Institute of Technology, Medak, Telangana for his consistent support.
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