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Performance Evaluation of GPSR Routing Protocol for VANETs using Bi-directional Coupling

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Routing in Vehicular Adhoc Networks is a challenging task where the nodes themselves are vehicles. The mobility factors such as beacon intervals and vehicles with different velocities may cause inaccuracy in the identification of the vehicle's position. This in turn affects the performance of the position based routing protocols. Further, there is a need to evaluate through simulations performance of the position based routing protocol, especially in urban realistic scenarios for VANETs. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing protocol (GPSR) for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. The simulations are done for various scenarios realizing the impact of mobility parameters on routing using GPSR, and performance is measured in terms of packet delivery ratio and throughput.

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Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 1 Performance Evaluation of GPSR Routing Protocol for VANETs using Bi-directional Coupling Dharani N.V. dharanimanoj@gmail.com Department of Computer Applications Dr.Ambedkar Institute of Technology Bengaluru-560056 India Shylaja B.S. shyla.au@gmail.com Department of Information Science Dr.Ambedkar Institute of Technology Bengaluru-560056 India Sree Lakshmi Ele. ele.sreelakshmi@gmail.com CCE, Indian Institute of Science UTL Technologies. Bengaluru-560022 India Abstract Routing in Vehicular Adhoc Networks is a challenging task where the nodes themselves are vehicles. The mobility factors such as beacon intervals and vehicles with different velocities may cause inaccuracy in the identification of the vehicle's position. This in turn affects the performance of the position based routing protocols. Further, there is a need to evaluate through simulations performance of the position based routing protocol, especially in urban realistic scenarios for VANETs. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing protocol (GPSR) for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. The simulations are done for various scenarios realizing the impact of mobility parameters on routing using GPSR, and performance is measured in terms of packet delivery ratio and throughput. Keywords: VANET, Bi-directional, GPSR, SUMO, OMNET++. 1. INTRODUCTION Vehicular Ad hoc Networks (VANETs) are an extension of Mobile ad-hoc networks (MANETs). The nodes in VANETs are the vehicles themselves which communicate with each other using wireless technology, without any pre-deployed infrastructure [1]. IEEE 802.11p standard is being used for the Wireless Access in Vehicular Environments [2]. Various applications of VANETs such as safety related and comfort related have been stated in[3] .The main factors effecting routing performance in VANET's are the speed of the vehicles, mobility constraints on the roads and frequent network breakdown. One of the preliminary tasks is in designing routing protocols which can trace the routes between vehicular nodes efficiently. For the same, realistic simulation scenarios are considered for routing protocols from which reliable results can be obtained. The objective of the work in this paper is to study the performance of GPSR through simulations for routing among vehicular nodes in VANETs particularly in urban areas. Mobility traces are obtained by the real world traffic simulator, these modelled offline traces will give the influence of road traffic on network traffic, but not vice versa. In order to overcome this problem bi-directional
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 2 coupling of traffic simulator SUMO [traffic simulator, http://sourceforge.net/projects/sumo/], and OMNET++/ INET Framework [network simulator, http://www.omnetpp.org/] are used for realistic simulation scenarios [4]. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing (GPSR) protocol for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment, bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. An overview of position based routing protocols of VANETs is presented in a tabular form in section 2. The comparative analysis is given in Section 3. And the Section 4 discusses on the methodology, simulation setup and its scenarios. Section 5 gives the evaluation metrics as well as an illustration of the acquired results. Further, Section 6 concludes the paper. 2. LITERATURE REVIEW Routing in VANETs is a challenging task because of the high speed of the nodes (vehicles), frequent topology changes and predictable mobility (constrained by the road topology and traffic regulations). Previous studies showed that the position based routing protocols outperforms non- position based protocols [5][6][7] as modern vehicles are equipped with GPS receivers, digital maps and navigation systems. The position based routing protocols use the geographical information of nodes to route the data packet towards the destination, by beacon packets. These beacon packets along with the node speed may introduce the inaccuracy for position information in the position based routing protocols [8][9]. Table1 shows the comparative study on different position based routing protocols and their functionalities in VANETs. The parameters chosen for comparison are the routing strategies, maps adopted, simulation scenarios and the different simulation tools. The protocols presented adopt multi-hop techniques to transmit the data from source to destination. As the GPSR protocol is the basic platform in position based routing protocol, it is considered further to evaluate its performance in Indian road network scenarios. GPSR makes greedy forwarding using the immediate neighbour’s position information in the network. It consists of two methods for forwarding the data packets. They are greedy forwarding and perimeter forwarding. It works well in a highway scenario because of evenly distributed nodes. GPSR may increase the possibility of getting the local maximum and link breakage because of the high mobility of vehicles and the road specifics in urban areas. It also suffers from link breakage with some stale neighbour nodes in the greedy mode because of the rapidly changing network topology. Packet loss and delay time may occur because the number of hops increases in perimeter mode forwarding. TABLE 1: Comparison and analysis of different position based routing protocols for VANETs. Routing protocol Forwarding Strategy Digital Map Traffi c- awar e Scenari o Recovery Strategy Interse ction Based Mobility Model Simulati on Tool GPSR Greedy No No Highway Perimeter Forwarding No Random Way Point NS2 GyTAR Improved Greedy Yes Yes Urban Carry and Forward Yes Realistic Mobility Model QualNet
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 3 GSR Greedy Yes No Urban Carry and Forward Yes Obtacle Model Daimler Chrysler GPSR-L Greedy No No Highway Perimeter Forwarding No Manhatta n NS2 CAR Advanced Greedy Yes No Urban& Highway Node Awareness Yes MTS NS2 A-STAR Greedy Yes Yes Urban Recompute d Anchor Path Yes M-Grid NS2 SAR Greedy Yes No Urban Flooding No RWP NS2 GPCR Greedy No No Urban Right hand rule Yes Obstacle Model Vanet Mobisim MDBG Greedy Yes No Urban Carry & Forward Yes MOVE NS2 JBGR Greedy Yes Yes Urban Carry & Forward Yes Vanet Mobisim Vanet Mobisim IBRP Greedy yes No Urban Carry & Forward Yes Manhatta n NS2 GTLBR Greedy Yes Yes Urban Carry & Forward Yes SUMO NS2/SU MO E-GyTAR Greedy Yes Yes Urban Carry& Forward Yes Vanet Mobisim GLOMO SIM BACRP Trajectory Yes Yes Urban Carry & Forward No Manhatta n NS2 IBGRP Greedy Yes No Urban -unknown- Yes - unknown- MatLab/ SIMULIN K 3. COMPARATIVE ANALYSIS Alsaqour et. al. analyzed the effect of position information inaccuracy caused by node speed and beacon packet interval time. Their work also identified that the network performance metrics can be affected by position information inaccuracy in GPSR routing protocol, in terms of end-to-end delay and routing loop in MANETs [26]. Yongjin et. al. and Shah et.al had also identified that the location errors degrade the performance of perimeter forwarding strategy in terms of data packet drop, optimal route and routing loop rate in dense networks and may lead to power consumption of
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 4 nodes due to sub-optimal path [27,28]. Further, the link connection problem with neighboring nodes and routing loop due to inaccurate location information are also identified as shown in [29, 30]. 4. SIMULATION ENVIRONMENT In the present study, analysis is carried out for network performance metrics, affected by position information inaccuracy in GPSR routing protocols, in term of PDR and Throughput. The speed of vehicular nodes and beacon packet interval time are the two main mobility parameters, which causes the position information inaccuracy in VANETs. Inaccurate location information caused by node mobility is also shown. 4.1 Simulation Model Network topology and route information on Nagarbhavi region in Bengaluru covering an area of 25 km2 are selected and downscaled from Open Street Map for the study. The information of network topology (net.xml) and Route files (rou.xml) are obtained using Net converter and Duarouter in SUMO. In a real time scenario, inter vehicle communication is necessary among the vehicle's for the distribution of the information on traffic, where the vehicles position depends on the received information. In order to handle such interactions, bi-directional coupling is required. Therefore, a TCP connection is used between Traffic and Network simulators to communicate bi-directionally using Traffic Control Interface (TraCI) [10], as shown in the figure 1. The bi-directional communication is initiated by sending the synchronization message and simulation results (vehicles position) to each other (figure 3). FIGURE 1: Methodology for calculating the Network performance metrics. By considering the urban scenario, vehicle speed (m/s) [in rou.xml] is modified during the generation of trace files in traffic simulator, which will be used further in network simulator. The beacon intervals in seconds and number of traffic sources [in .ini file] is varied for the communication between nodes. The moving vehicles on the obtained road network are given in figure 2a &b.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 5 FIGURE 2 a & b: Road network of Nagarbhavi [urban area] showing the simulation of Nodes in SUMO [Traffic simulator]. The vehicular mobility is controlled by SUMO and Vehicular nodes by OMNET++/INET, where IEEE 8011p is used for the communication. The position and radio wave transmissions between the vehicular nodes are shown in the figure 3.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 6 FIGURE 3: Communication among the vehicles in motion [OMNET++/INET]. Table 2 indicates the parameters used for network operation, where the parameters of Physical and MAC layers are configured to IEEE 802.11p. TABLE 2: Configuration parameters used in the simulation process. Parameter(s) Value(s) Simulation Area 5000m*5000m Simulation Time 300s,600s Number of traffic Sources 10,20,50,70,100 Vehicle Speed 5m/s,10m/s,15m/s,20m/s Data Packet Length 512 Byte Vehicle Beacon Interval 1s,2s,3s,4s,5s Carrier Frequency 5.8GHz Transmission Range 250m Physical Layer IEEE802.11p Data Bitrates 27Mbps Transmission Power 10mW Packet Type UDP Mobility Model TraCIMobility Routing Protocol GPSR 5. RESULTS AND DISCUSSION The performance of chosen GPSR routing protocol is evaluated for different parameters which includes beacon intervals, vehicles with different velocities and numerous traffic sources. The PDR and throughput are the two different network performance metrics evaluated for the comparison of GPSR protocol performance. Packet Delivery Ratio (PDR) gives the ratio of the number of data packets received at the destination vehicle to the number of data packets sent by the source vehicle. The throughput is the total number of bits delivered successfully from the source to the destination every second. The results obtained through simulation are discussed below. 5.1 Varying Beacon Packet Interval Figure 4 show the simulation results on the effect of using different beacon intervals. It shows the performance metrics, PDR and Throughput of GPSR routing protocol for Beacon packet intervals varying from 1 second to 6 seconds keeping the maximum velocity of a vehicle as constant to 5m/s. The result indicates the degradation of the protocol performance when the time gap for beacon packet increases. The result also shows an inverse relation between PDR, Throughput and Beacon Packet Intervals due to the inaccuracy on the delivery of position information of neighbors.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 7 FIGURE 4: The relationship between PDR, Throughput and Beacon Intervals. 5.2 Vehicles with Varying Velocities Figure 5 shows the effect of node speed on the performance of GPSR routing protocol in term of PDR and Throughput for node velocities starting from 5m/s to 20m/s in steps of 5m/s. The beacon interval is set as 1.5 second in network simulator. Due to the network disconnection and path instability the performance of GPSR decreases as the speed of the node increases. Vehicle speed influences the accuracy in receiving the geographical information of nodes which effect the performance of GPSR. FIGURE 5: The impact of vehicle Speed on PDR and Throughput. 5.3 Traffic sources (nodes transferring the data packets) The levels of Throughput and PDR relies on the number of traffic sources. As the traffic sources increases, the throughput increases because of the increase in transmission rate of data packets. This helps in the improvement of connectivity between traffic sources. In the meantime, the PDR decreases as there is a lack of scalability. Also, drastic changes can be observed in PDR due to node buffer overflow, as shown in the figure 6.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 8 FIGURE 6: Influence of Traffic Sources on PDR and Throughput. 6. CONCLUSION In this paper, an attempt has been made to study the effect of node speed and beacon intervals on GPSR protocol performance. Network topology and route information about Nagarbhavi region, Bengaluru urban area is obtained using OpenStreetMap (http://www.openstreetmap.org/). The bi- directional coupling of OMNET++/INET and SUMO had been used to create a realistic scenario. The results indicate that:  The levels in beacon intervals have an impact on the delivery of position information degrading the performance of GPSR.  High mobility of vehicles causing network disconnection and path stability problem influences the network performance metrics.  As the number of traffic sources increase the PDR decreases due to scalability issue in GPSR. The present study on the performance of GPSR routing protocol indicates the potential to improve the performance for VANETs in urban scenarios considering the real time parameters such as vehicles velocity, direction and vehicle density for further work. 7. ACKNOWLEDGEMENT The authors would like to thank the web sources for SUMO (http://sourceforge.net/projects/sumo/), Vein (http://veins.car2x.org/) and OMNET++/INET (http://www.omnetpp.org/) software's. We would also like to express our gratitude to our colleagues and management for the overall support. 8. REFERENCES [1] Bernsen J. and Manivannan D., "Unicast routing protocols for vehicular ad hoc networks: A critical comparison and classification". Pervasive Mobile Computing, Vol.5, 2009, pp: 1��18. [2] Jiang D. and Delgrossi L., “IEEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments”. In Proceedings of Vehicular Technology Conference, 2008, pp. 55-59.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 9 [3] Bai, Fan and Elbatt, Tamer and Hollan, Gavin and Krishnan, Hariharan and Sadekar, Varsha." Towards characterizing and classifying communication-based automotive applications from a wireless networking perspective". In Proceedings of IEEE Workshop on Automotive Networking and Applications, 2006, pp: 1-25. [4] Christoph Sommer, Reinhard German, and Falko Dressler., "Bidirectional Coupled Network and Road Traffic Simulation for Improved IVC Analysis". IEEE Transactions on Mobile Computing, Vol. 10, 2011. [5] Sardar Muhammad Bilal,Carlos Jesus Bernardos and Carmen Guerrero., "Position-based routing in Vehicular Networks: A survey". Journal of Networks and Computer Applications, pp: 685-697, 2013. [6] Misbah Jadoon,Sajjad Madani,Khizar Hayat., "Location and Non-Location Based Ad-hoc Routing Protocols under various Mobility Models :A Comparative Study." The International Arab Journal of Information Technology, Vol 9, 2012. [7] Santos R. A., Edwards R. M., Seed L. N. and Edwards A., " A Location-based routing algorithm for Vehicle to Vehicle communication." in Proceedings of IEEE 13th International Conference on Computer Communications and Networks, 2004 pp: 221-226. [8] Fubler H., Mauve M., Hartenstein H., Kasemann M., and Vollmer D. “Location Based Routing for Vehicular Ad Hoc Networks.” Computer Journal of ACM SIGMOBILE Mobile Computing and Communications Review, vol. 7, pp: 4749, 2003. [9] Tsumochi, J., Masayama, K., Uehara, H., and Yokoyama, M., “Impact of mobility Metric on Routing Protocols for Mobile Ad Hoc Networks.” in Proceedings of IEEE Pacific Rim Conference on Communication, Computers and Signal Processing, Vol 1, 2003, pp: 322- 325 [10] Kwon, S. and Shroff, N.B. “Geographic routing in the presence of location errors,” The international journal of computer and telecommunications networking, Vol 50, pp: 2902-2917, 2006. [11] Karp B. and Kung H. T., “GPSR: greedy perimeter stateless Routing for wireless networks,” in Proceedings of the 6th Annual International Conference on Mobile Computing and Networking 2000, pp: 243–254. [12] Moez Jerb, Sidi-Mohammed Senouci, Rabah Meraihi and Yacine Ghamri-Doudan., "An Improved Vehicular Ad Hoc Routing Protocol for City Environments." in proceedings of IEEE International Conference on communication, 2007, pp: 3972-3979. [13] C. Lochert, H. Hartenstein, J. Tian, D. Herrmann, H. Fler, and M. Mauve., " A routing strategy for vehicular ad hoc networks in city environments," in Proceedings of IEEE Intelligent Vehicles Symposium (IV2003), 2003, pp: 156-161. [14] Sunder Aditya Rao et al.,” GPSR-L: Greedy Perimeter Stateless Routing with Lifetime for VANETS,” IEEE Proc. 8th Int. Conf. on ITS Telecommunication,, pp: 299-304, 2008. [15] Valery Naumov and Thomas R. Gross., “Connectivity-Aware Routing (CAR) in Vehicular AdHoc Networks”, in Proceedings of IEEE InfoCOM, 2007, Vol 26, pp: 1919-1927. [16] Boon-Chong Seet, Genping Liu, Bu-Sung Lee, Chuan-Heng Foh, Kai-Juan Wong, and Keok- Kee Lee., A-STAR: A mobile ad hoc routing strategy for metropolis vehicular communications. In Networking 2004, pages 989–999. Springer, 2004.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 10 [17] Jing Tian et al., “Spatially Aware Packet Routing for Mobile Ad Hoc Inter-Vehicle Radio Networks”, in proceedings of IEEE Intelligent Transportation Systems, 2003, pp: 1546 – 1551. [18] C Lochert, M Mauve, H Fera, and H Hartenstein, “Geographic routing in city scenarios”, ACM SIGMOBILE Mobile Computing and Communication, Vol 9, pp: 89-72, 2005. [19] Jang, Hung-Chin, and Hsiang-Te Huang. "Moving Direction Based Greedy routing algorithm for VANET." in proceedings of IEEE Computer Symposium (ICS), 2010, pp: 535-540, [20] Tsiachris, Sotirios, Georgios Koltsidas, and Fotini-Niovi Pavlidou. "Junction-based geographic routing algorithm for vehicular ad hoc networks." Springer Wireless personal communications, pp: 955-973. 2013. [21] Chou, Li-Der and Yang, Jyun-Yan and Hsieh, Ying-Cheng and Chang, Der-Chyn and Tung, Chi-Feng "Intersection-based routing protocol for VANETs", Springer Wireless personal communications, Vol 60, pp:105-124, 2011 [22] Li, Hui and Guo, Aihuang and Li, Guangyu " Geographic and traffic load based routing strategy for VANET in urban traffic environment ", in proceedings of IET 3rd International Conference on Wireless, 2010, pp: 6-9. [23] Sardar Bilal, Sajjad Madani, and Imran Khan “Enhanced Junction Selection Mechanism for Routing Protocol in VANETs”, The International Arab Journal of Information Technology, Vol. 8, 2011. [24] Lai, Wei Kuang and Yang, Kai-Ting and Li, Meng-Chong " Bus assisted connectionless routing protocol for metropolitan VANET" in proceedings of IEEE Fifth International Conference on Genetic and Evolutionary Computing, 2011, pp: 57-60. [25] Hanan Saleet,Rami Langar, Kshirasagar Naik, Raouf Boutaba, Amiya Nayak, Nishith Goel., "Intersection-Based Geographical Routing Protocol for VANETs: A Proposal and Analysis" IEEE Transactions on Vehicular Technology, Vol. 60, 2011. [26] Alsaqour, Raed, Mohamad Shanudin, Mahamod Ismail, and Maha Abdelhaq., "Analysis of mobility parameters effect on position information inaccuracy of GPSR position-based MANET Routing Protocol." Journal of Theoretical & Applied Information Technology Vol 28, 2011. [27] Shah, R.C, Wolisz, A, and Rabaey, J.M., “On the performance of geographical routing in the presence of localization errors”, IEEE International Conference on Communications. ICC 2005, vol 5, pp: 2979-2985, 2005. [28] Yongjin, K, Jae-Joon, L, and Ahmed, H., “Modeling and Analyzing the Impact of Location Inconsistencies on Geographic Routing in Wireless Networks,” ACM SIGMOBILE Mobile Computing and Communications Review, vol. 8, pp: 4860.2004 [29] Kwon, S., Shroff, N.B., “Geographic routing in the presence of location errors,” The international journal of computer and telecommunications networking, vol 50, pp: 2902- 2917,2006. [30] Son, Dongjin, Ahmed Helmy, and Bhaskar Krishnamachari., "The effect of mobility-induced location errors on geographic routing in ad hoc networks: analysis and improvement using mobility prediction." In Wireless Communications and Networking Conference, 2004. WCNC. vol. 1, pp: 189-194, 2004.
Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 11 9. ANNEXURE 1. Greedy Perimeter Stateless Routing Protocol (GPSR) [11] 2. Improved Greedy Traffic Aware Routing Protocol (GyTAR) [12] 3. Geographic Source Routing (GSR) [13] 4. Greedy Perimeter Stateless Routing with Lifetime (GPSR-L) [14] 5. Connectivity-Aware Routing (CAR) [15] 6. Anchor-based Street and Traffic Aware Routing (A-STAR) [16] 7. Spatially Aware packet Routing (SAR) [17] 8. Greedy Perimeter Coordinator Routing (GPCR) [18] 9. Moving Direction Based Greedy Routing (MDBG) [19] 10. Junction-Based Geographic Routing (JBGR) [20] 11. Intersection-Based Routing Protocol (IBRP) [21] 12. Geographic and Traffic Load Based Routing Strategy (GTLBR) [22] 13. Enhanced GyTAR (E- GyTAR)[23] 14. Bus Assisted Connectionless Routing Protocol (BACRP)[24] 15 Intersection-Based Geographical Routing Protocol (IBGRP)[25]

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Performance Evaluation of GPSR Routing Protocol for VANETs using Bi-directional Coupling

  • 1. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 1 Performance Evaluation of GPSR Routing Protocol for VANETs using Bi-directional Coupling Dharani N.V. dharanimanoj@gmail.com Department of Computer Applications Dr.Ambedkar Institute of Technology Bengaluru-560056 India Shylaja B.S. shyla.au@gmail.com Department of Information Science Dr.Ambedkar Institute of Technology Bengaluru-560056 India Sree Lakshmi Ele. ele.sreelakshmi@gmail.com CCE, Indian Institute of Science UTL Technologies. Bengaluru-560022 India Abstract Routing in Vehicular Adhoc Networks is a challenging task where the nodes themselves are vehicles. The mobility factors such as beacon intervals and vehicles with different velocities may cause inaccuracy in the identification of the vehicle's position. This in turn affects the performance of the position based routing protocols. Further, there is a need to evaluate through simulations performance of the position based routing protocol, especially in urban realistic scenarios for VANETs. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing protocol (GPSR) for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. The simulations are done for various scenarios realizing the impact of mobility parameters on routing using GPSR, and performance is measured in terms of packet delivery ratio and throughput. Keywords: VANET, Bi-directional, GPSR, SUMO, OMNET++. 1. INTRODUCTION Vehicular Ad hoc Networks (VANETs) are an extension of Mobile ad-hoc networks (MANETs). The nodes in VANETs are the vehicles themselves which communicate with each other using wireless technology, without any pre-deployed infrastructure [1]. IEEE 802.11p standard is being used for the Wireless Access in Vehicular Environments [2]. Various applications of VANETs such as safety related and comfort related have been stated in[3] .The main factors effecting routing performance in VANET's are the speed of the vehicles, mobility constraints on the roads and frequent network breakdown. One of the preliminary tasks is in designing routing protocols which can trace the routes between vehicular nodes efficiently. For the same, realistic simulation scenarios are considered for routing protocols from which reliable results can be obtained. The objective of the work in this paper is to study the performance of GPSR through simulations for routing among vehicular nodes in VANETs particularly in urban areas. Mobility traces are obtained by the real world traffic simulator, these modelled offline traces will give the influence of road traffic on network traffic, but not vice versa. In order to overcome this problem bi-directional
  • 2. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 2 coupling of traffic simulator SUMO [traffic simulator, http://sourceforge.net/projects/sumo/], and OMNET++/ INET Framework [network simulator, http://www.omnetpp.org/] are used for realistic simulation scenarios [4]. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing (GPSR) protocol for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment, bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. An overview of position based routing protocols of VANETs is presented in a tabular form in section 2. The comparative analysis is given in Section 3. And the Section 4 discusses on the methodology, simulation setup and its scenarios. Section 5 gives the evaluation metrics as well as an illustration of the acquired results. Further, Section 6 concludes the paper. 2. LITERATURE REVIEW Routing in VANETs is a challenging task because of the high speed of the nodes (vehicles), frequent topology changes and predictable mobility (constrained by the road topology and traffic regulations). Previous studies showed that the position based routing protocols outperforms non- position based protocols [5][6][7] as modern vehicles are equipped with GPS receivers, digital maps and navigation systems. The position based routing protocols use the geographical information of nodes to route the data packet towards the destination, by beacon packets. These beacon packets along with the node speed may introduce the inaccuracy for position information in the position based routing protocols [8][9]. Table1 shows the comparative study on different position based routing protocols and their functionalities in VANETs. The parameters chosen for comparison are the routing strategies, maps adopted, simulation scenarios and the different simulation tools. The protocols presented adopt multi-hop techniques to transmit the data from source to destination. As the GPSR protocol is the basic platform in position based routing protocol, it is considered further to evaluate its performance in Indian road network scenarios. GPSR makes greedy forwarding using the immediate neighbour’s position information in the network. It consists of two methods for forwarding the data packets. They are greedy forwarding and perimeter forwarding. It works well in a highway scenario because of evenly distributed nodes. GPSR may increase the possibility of getting the local maximum and link breakage because of the high mobility of vehicles and the road specifics in urban areas. It also suffers from link breakage with some stale neighbour nodes in the greedy mode because of the rapidly changing network topology. Packet loss and delay time may occur because the number of hops increases in perimeter mode forwarding. TABLE 1: Comparison and analysis of different position based routing protocols for VANETs. Routing protocol Forwarding Strategy Digital Map Traffi c- awar e Scenari o Recovery Strategy Interse ction Based Mobility Model Simulati on Tool GPSR Greedy No No Highway Perimeter Forwarding No Random Way Point NS2 GyTAR Improved Greedy Yes Yes Urban Carry and Forward Yes Realistic Mobility Model QualNet
  • 3. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 3 GSR Greedy Yes No Urban Carry and Forward Yes Obtacle Model Daimler Chrysler GPSR-L Greedy No No Highway Perimeter Forwarding No Manhatta n NS2 CAR Advanced Greedy Yes No Urban& Highway Node Awareness Yes MTS NS2 A-STAR Greedy Yes Yes Urban Recompute d Anchor Path Yes M-Grid NS2 SAR Greedy Yes No Urban Flooding No RWP NS2 GPCR Greedy No No Urban Right hand rule Yes Obstacle Model Vanet Mobisim MDBG Greedy Yes No Urban Carry & Forward Yes MOVE NS2 JBGR Greedy Yes Yes Urban Carry & Forward Yes Vanet Mobisim Vanet Mobisim IBRP Greedy yes No Urban Carry & Forward Yes Manhatta n NS2 GTLBR Greedy Yes Yes Urban Carry & Forward Yes SUMO NS2/SU MO E-GyTAR Greedy Yes Yes Urban Carry& Forward Yes Vanet Mobisim GLOMO SIM BACRP Trajectory Yes Yes Urban Carry & Forward No Manhatta n NS2 IBGRP Greedy Yes No Urban -unknown- Yes - unknown- MatLab/ SIMULIN K 3. COMPARATIVE ANALYSIS Alsaqour et. al. analyzed the effect of position information inaccuracy caused by node speed and beacon packet interval time. Their work also identified that the network performance metrics can be affected by position information inaccuracy in GPSR routing protocol, in terms of end-to-end delay and routing loop in MANETs [26]. Yongjin et. al. and Shah et.al had also identified that the location errors degrade the performance of perimeter forwarding strategy in terms of data packet drop, optimal route and routing loop rate in dense networks and may lead to power consumption of
  • 4. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 4 nodes due to sub-optimal path [27,28]. Further, the link connection problem with neighboring nodes and routing loop due to inaccurate location information are also identified as shown in [29, 30]. 4. SIMULATION ENVIRONMENT In the present study, analysis is carried out for network performance metrics, affected by position information inaccuracy in GPSR routing protocols, in term of PDR and Throughput. The speed of vehicular nodes and beacon packet interval time are the two main mobility parameters, which causes the position information inaccuracy in VANETs. Inaccurate location information caused by node mobility is also shown. 4.1 Simulation Model Network topology and route information on Nagarbhavi region in Bengaluru covering an area of 25 km2 are selected and downscaled from Open Street Map for the study. The information of network topology (net.xml) and Route files (rou.xml) are obtained using Net converter and Duarouter in SUMO. In a real time scenario, inter vehicle communication is necessary among the vehicle's for the distribution of the information on traffic, where the vehicles position depends on the received information. In order to handle such interactions, bi-directional coupling is required. Therefore, a TCP connection is used between Traffic and Network simulators to communicate bi-directionally using Traffic Control Interface (TraCI) [10], as shown in the figure 1. The bi-directional communication is initiated by sending the synchronization message and simulation results (vehicles position) to each other (figure 3). FIGURE 1: Methodology for calculating the Network performance metrics. By considering the urban scenario, vehicle speed (m/s) [in rou.xml] is modified during the generation of trace files in traffic simulator, which will be used further in network simulator. The beacon intervals in seconds and number of traffic sources [in .ini file] is varied for the communication between nodes. The moving vehicles on the obtained road network are given in figure 2a &b.
  • 5. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 5 FIGURE 2 a & b: Road network of Nagarbhavi [urban area] showing the simulation of Nodes in SUMO [Traffic simulator]. The vehicular mobility is controlled by SUMO and Vehicular nodes by OMNET++/INET, where IEEE 8011p is used for the communication. The position and radio wave transmissions between the vehicular nodes are shown in the figure 3.
  • 6. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 6 FIGURE 3: Communication among the vehicles in motion [OMNET++/INET]. Table 2 indicates the parameters used for network operation, where the parameters of Physical and MAC layers are configured to IEEE 802.11p. TABLE 2: Configuration parameters used in the simulation process. Parameter(s) Value(s) Simulation Area 5000m*5000m Simulation Time 300s,600s Number of traffic Sources 10,20,50,70,100 Vehicle Speed 5m/s,10m/s,15m/s,20m/s Data Packet Length 512 Byte Vehicle Beacon Interval 1s,2s,3s,4s,5s Carrier Frequency 5.8GHz Transmission Range 250m Physical Layer IEEE802.11p Data Bitrates 27Mbps Transmission Power 10mW Packet Type UDP Mobility Model TraCIMobility Routing Protocol GPSR 5. RESULTS AND DISCUSSION The performance of chosen GPSR routing protocol is evaluated for different parameters which includes beacon intervals, vehicles with different velocities and numerous traffic sources. The PDR and throughput are the two different network performance metrics evaluated for the comparison of GPSR protocol performance. Packet Delivery Ratio (PDR) gives the ratio of the number of data packets received at the destination vehicle to the number of data packets sent by the source vehicle. The throughput is the total number of bits delivered successfully from the source to the destination every second. The results obtained through simulation are discussed below. 5.1 Varying Beacon Packet Interval Figure 4 show the simulation results on the effect of using different beacon intervals. It shows the performance metrics, PDR and Throughput of GPSR routing protocol for Beacon packet intervals varying from 1 second to 6 seconds keeping the maximum velocity of a vehicle as constant to 5m/s. The result indicates the degradation of the protocol performance when the time gap for beacon packet increases. The result also shows an inverse relation between PDR, Throughput and Beacon Packet Intervals due to the inaccuracy on the delivery of position information of neighbors.
  • 7. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 7 FIGURE 4: The relationship between PDR, Throughput and Beacon Intervals. 5.2 Vehicles with Varying Velocities Figure 5 shows the effect of node speed on the performance of GPSR routing protocol in term of PDR and Throughput for node velocities starting from 5m/s to 20m/s in steps of 5m/s. The beacon interval is set as 1.5 second in network simulator. Due to the network disconnection and path instability the performance of GPSR decreases as the speed of the node increases. Vehicle speed influences the accuracy in receiving the geographical information of nodes which effect the performance of GPSR. FIGURE 5: The impact of vehicle Speed on PDR and Throughput. 5.3 Traffic sources (nodes transferring the data packets) The levels of Throughput and PDR relies on the number of traffic sources. As the traffic sources increases, the throughput increases because of the increase in transmission rate of data packets. This helps in the improvement of connectivity between traffic sources. In the meantime, the PDR decreases as there is a lack of scalability. Also, drastic changes can be observed in PDR due to node buffer overflow, as shown in the figure 6.
  • 8. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 8 FIGURE 6: Influence of Traffic Sources on PDR and Throughput. 6. CONCLUSION In this paper, an attempt has been made to study the effect of node speed and beacon intervals on GPSR protocol performance. Network topology and route information about Nagarbhavi region, Bengaluru urban area is obtained using OpenStreetMap (http://www.openstreetmap.org/). The bi- directional coupling of OMNET++/INET and SUMO had been used to create a realistic scenario. The results indicate that:  The levels in beacon intervals have an impact on the delivery of position information degrading the performance of GPSR.  High mobility of vehicles causing network disconnection and path stability problem influences the network performance metrics.  As the number of traffic sources increase the PDR decreases due to scalability issue in GPSR. The present study on the performance of GPSR routing protocol indicates the potential to improve the performance for VANETs in urban scenarios considering the real time parameters such as vehicles velocity, direction and vehicle density for further work. 7. ACKNOWLEDGEMENT The authors would like to thank the web sources for SUMO (http://sourceforge.net/projects/sumo/), Vein (http://veins.car2x.org/) and OMNET++/INET (http://www.omnetpp.org/) software's. We would also like to express our gratitude to our colleagues and management for the overall support. 8. REFERENCES [1] Bernsen J. and Manivannan D., "Unicast routing protocols for vehicular ad hoc networks: A critical comparison and classification". Pervasive Mobile Computing, Vol.5, 2009, pp: 1–18. [2] Jiang D. and Delgrossi L., “IEEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments”. In Proceedings of Vehicular Technology Conference, 2008, pp. 55-59.
  • 9. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 9 [3] Bai, Fan and Elbatt, Tamer and Hollan, Gavin and Krishnan, Hariharan and Sadekar, Varsha." Towards characterizing and classifying communication-based automotive applications from a wireless networking perspective". In Proceedings of IEEE Workshop on Automotive Networking and Applications, 2006, pp: 1-25. [4] Christoph Sommer, Reinhard German, and Falko Dressler., "Bidirectional Coupled Network and Road Traffic Simulation for Improved IVC Analysis". IEEE Transactions on Mobile Computing, Vol. 10, 2011. [5] Sardar Muhammad Bilal,Carlos Jesus Bernardos and Carmen Guerrero., "Position-based routing in Vehicular Networks: A survey". Journal of Networks and Computer Applications, pp: 685-697, 2013. [6] Misbah Jadoon,Sajjad Madani,Khizar Hayat., "Location and Non-Location Based Ad-hoc Routing Protocols under various Mobility Models :A Comparative Study." The International Arab Journal of Information Technology, Vol 9, 2012. [7] Santos R. A., Edwards R. M., Seed L. N. and Edwards A., " A Location-based routing algorithm for Vehicle to Vehicle communication." in Proceedings of IEEE 13th International Conference on Computer Communications and Networks, 2004 pp: 221-226. [8] Fubler H., Mauve M., Hartenstein H., Kasemann M., and Vollmer D. “Location Based Routing for Vehicular Ad Hoc Networks.” Computer Journal of ACM SIGMOBILE Mobile Computing and Communications Review, vol. 7, pp: 4749, 2003. [9] Tsumochi, J., Masayama, K., Uehara, H., and Yokoyama, M., “Impact of mobility Metric on Routing Protocols for Mobile Ad Hoc Networks.” in Proceedings of IEEE Pacific Rim Conference on Communication, Computers and Signal Processing, Vol 1, 2003, pp: 322- 325 [10] Kwon, S. and Shroff, N.B. “Geographic routing in the presence of location errors,” The international journal of computer and telecommunications networking, Vol 50, pp: 2902-2917, 2006. [11] Karp B. and Kung H. T., “GPSR: greedy perimeter stateless Routing for wireless networks,” in Proceedings of the 6th Annual International Conference on Mobile Computing and Networking 2000, pp: 243–254. [12] Moez Jerb, Sidi-Mohammed Senouci, Rabah Meraihi and Yacine Ghamri-Doudan., "An Improved Vehicular Ad Hoc Routing Protocol for City Environments." in proceedings of IEEE International Conference on communication, 2007, pp: 3972-3979. [13] C. Lochert, H. Hartenstein, J. Tian, D. Herrmann, H. Fler, and M. Mauve., " A routing strategy for vehicular ad hoc networks in city environments," in Proceedings of IEEE Intelligent Vehicles Symposium (IV2003), 2003, pp: 156-161. [14] Sunder Aditya Rao et al.,” GPSR-L: Greedy Perimeter Stateless Routing with Lifetime for VANETS,” IEEE Proc. 8th Int. Conf. on ITS Telecommunication,, pp: 299-304, 2008. [15] Valery Naumov and Thomas R. Gross., “Connectivity-Aware Routing (CAR) in Vehicular AdHoc Networks”, in Proceedings of IEEE InfoCOM, 2007, Vol 26, pp: 1919-1927. [16] Boon-Chong Seet, Genping Liu, Bu-Sung Lee, Chuan-Heng Foh, Kai-Juan Wong, and Keok- Kee Lee., A-STAR: A mobile ad hoc routing strategy for metropolis vehicular communications. In Networking 2004, pages 989–999. Springer, 2004.
  • 10. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 10 [17] Jing Tian et al., “Spatially Aware Packet Routing for Mobile Ad Hoc Inter-Vehicle Radio Networks”, in proceedings of IEEE Intelligent Transportation Systems, 2003, pp: 1546 – 1551. [18] C Lochert, M Mauve, H Fera, and H Hartenstein, “Geographic routing in city scenarios”, ACM SIGMOBILE Mobile Computing and Communication, Vol 9, pp: 89-72, 2005. [19] Jang, Hung-Chin, and Hsiang-Te Huang. "Moving Direction Based Greedy routing algorithm for VANET." in proceedings of IEEE Computer Symposium (ICS), 2010, pp: 535-540, [20] Tsiachris, Sotirios, Georgios Koltsidas, and Fotini-Niovi Pavlidou. "Junction-based geographic routing algorithm for vehicular ad hoc networks." Springer Wireless personal communications, pp: 955-973. 2013. [21] Chou, Li-Der and Yang, Jyun-Yan and Hsieh, Ying-Cheng and Chang, Der-Chyn and Tung, Chi-Feng "Intersection-based routing protocol for VANETs", Springer Wireless personal communications, Vol 60, pp:105-124, 2011 [22] Li, Hui and Guo, Aihuang and Li, Guangyu " Geographic and traffic load based routing strategy for VANET in urban traffic environment ", in proceedings of IET 3rd International Conference on Wireless, 2010, pp: 6-9. [23] Sardar Bilal, Sajjad Madani, and Imran Khan “Enhanced Junction Selection Mechanism for Routing Protocol in VANETs”, The International Arab Journal of Information Technology, Vol. 8, 2011. [24] Lai, Wei Kuang and Yang, Kai-Ting and Li, Meng-Chong " Bus assisted connectionless routing protocol for metropolitan VANET" in proceedings of IEEE Fifth International Conference on Genetic and Evolutionary Computing, 2011, pp: 57-60. [25] Hanan Saleet,Rami Langar, Kshirasagar Naik, Raouf Boutaba, Amiya Nayak, Nishith Goel., "Intersection-Based Geographical Routing Protocol for VANETs: A Proposal and Analysis" IEEE Transactions on Vehicular Technology, Vol. 60, 2011. [26] Alsaqour, Raed, Mohamad Shanudin, Mahamod Ismail, and Maha Abdelhaq., "Analysis of mobility parameters effect on position information inaccuracy of GPSR position-based MANET Routing Protocol." Journal of Theoretical & Applied Information Technology Vol 28, 2011. [27] Shah, R.C, Wolisz, A, and Rabaey, J.M., “On the performance of geographical routing in the presence of localization errors”, IEEE International Conference on Communications. ICC 2005, vol 5, pp: 2979-2985, 2005. [28] Yongjin, K, Jae-Joon, L, and Ahmed, H., “Modeling and Analyzing the Impact of Location Inconsistencies on Geographic Routing in Wireless Networks,” ACM SIGMOBILE Mobile Computing and Communications Review, vol. 8, pp: 4860.2004 [29] Kwon, S., Shroff, N.B., “Geographic routing in the presence of location errors,” The international journal of computer and telecommunications networking, vol 50, pp: 2902- 2917,2006. [30] Son, Dongjin, Ahmed Helmy, and Bhaskar Krishnamachari., "The effect of mobility-induced location errors on geographic routing in ad hoc networks: analysis and improvement using mobility prediction." In Wireless Communications and Networking Conference, 2004. WCNC. vol. 1, pp: 189-194, 2004.
  • 11. Dharani N. V, Shylaja B. S & Sree Lakshmi. Ele International Journal of Computer Networks (IJCN), Volume (7) : Issue (1) : 2015 11 9. ANNEXURE 1. Greedy Perimeter Stateless Routing Protocol (GPSR) [11] 2. Improved Greedy Traffic Aware Routing Protocol (GyTAR) [12] 3. Geographic Source Routing (GSR) [13] 4. Greedy Perimeter Stateless Routing with Lifetime (GPSR-L) [14] 5. Connectivity-Aware Routing (CAR) [15] 6. Anchor-based Street and Traffic Aware Routing (A-STAR) [16] 7. Spatially Aware packet Routing (SAR) [17] 8. Greedy Perimeter Coordinator Routing (GPCR) [18] 9. Moving Direction Based Greedy Routing (MDBG) [19] 10. Junction-Based Geographic Routing (JBGR) [20] 11. Intersection-Based Routing Protocol (IBRP) [21] 12. Geographic and Traffic Load Based Routing Strategy (GTLBR) [22] 13. Enhanced GyTAR (E- GyTAR)[23] 14. Bus Assisted Connectionless Routing Protocol (BACRP)[24] 15 Intersection-Based Geographical Routing Protocol (IBGRP)[25]