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  1. 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 547 AN EMPIRICAL STUDY TO COMPARE BETWEEN IEEE 802.11P AND WAVE PROTOCOLS IN VANETS NETWORKS Mostafa M. El-Said College of Engineering and Computing, Grand Valley State University, Allendale, Michigan, USA ABSTRACT Vehicular ad hoc networks (VANETs) are a class of ad hoc networks that are designed to improve travelers’ safety, entertain travelers, and reduce fuel consumption and pollution. One of the main challenges facing the VANETs deployment is network scalability, both in sparse and dense network environments. Network scalability is defined as the network’s ability to handle the admission and the hands-off of mobile VANET nodes without suffering a noticeable loss in performance. This work studied the contributing factors to the VANET network scalability problem and proposes a solution based on the use of the IEEE802.11P and the IEEEE 802.11P with multi- channels support standard. In this work, safety data is assumed to be available and hosted in a secure back-end server. Promising results were obtained using NCTUns simulation engine that show that VANETs networks’ performance running under IEEE802.11P with multi-channel support outperform its correspondence running under IEEE802.11P only. Keywords: IEEE802.11P, WAVE, VANETs Simulation. 1. INTRODUCTION VANETs networks are an effort to make the Intelligent Transportation System (ITS) reality by allowing the exchange of road traffic information or information of vehicles’ best interest such as the nearest gas station or parking garage. In consequence, drivers can react promptly to road critical situations events (such as the car in front of you suddenly broke down) by choosing an alternative route as quickly as possible or proceed to the nearest gas station or parking garage [1, 2, 3 and 4]. In VANETs, vehicles are the only mobile nodes in the network system. Each vehicle has an on board unit (OBU), that is cable of exchanging traffic alert messages including road conditions and other vehicles’ position, speed, ..etc. Mobile nodes transmit data using two VANETs architectures: (i) INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), pp. 547-555 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET © I A E M E
  2. 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 548 Inter-Vehicle Communications (IVC) and (ii) Roadside-to-Vehicle Communication (RVC). In IVC architecture, vehicles are equipped with one or more wireless adapter (multi-adapters node). They communicate directly with others that are within communication range. In RVC architecture, fixed units are known as Roadside Assistance Units (RSU), which collects the road conditions traffic and disseminates it to VANETs nodes that are within its communication range. RSU may receive this information from the wired network via a central traffic server. The traffic server aggregates traffic information from a traffic cloud and ensure its correctness and data authenticity [5, 6, 7, 8 and 12]. There are two categories of MAC protocols that support data transmission in VANETs environment: (i) The first protocol is defined by the IEEE 802.11P and uses acontention-based (Carrier Sense Multiplex Access with Collision Avoidance (CSMA/CA) protocol with full implementation of node joining process including node probing, association and authentication. (ii) The second protocol is a family of protocols defined by the IEEE 802.11P and the IEEE 1609. The 802.11P protocol uses the Wireless Access in Vehicular Environments (WAVE) with multi-channels extension supported by the IEEE 1609.4 protocol at the upper layers. The system diagram of WAVE communications is shown in Figure 1. The WAVE enabled OBU and the RSU units implement a full stack of the WAVE modules. IEEE 1609.1 WAVE Resource Manager Application Layer IEEE 1609.3 Networking Services IEEE 1609.2 Security Services Transport, Network and Logical Link Layers IEEE 1609.4 Multi-Channel Operations (MAC- Extension) Medium Access Layer IEEE 802.11P WAVE MAC IEEE 802.11P WAVE PHY Physical Layer Figure 1 WAVE system protocol stack. Figure is based in [10], [11] In 1999, the Federal Communication Commission (FCC) allocated a 75 MHz of Dedicated Short Range Communication (DSRC) frequency band in the 5.850-5.925GHz for ITS WAVE based system utilization. This frequency band is divided into seven channels with 10 MHZ each. The IEEE 1609 family standards define two types of communication channels in WAVE based systems to support safety and non-safety applications. The first channel is called Control Channel (CCH) which is used to transmit WAVE Short Messages (WSMs) and announce WAVE services. The second channel is known as Service Channel (SCH), which is used to transmit application/service data. In any WAVE based system, only one CCH and one or more SCH will be needed such as described in figure 2. Using more than one SCH will depend on the application requirements and the available bandwidth [12].
  3. 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 549 Figure 2 Distribution of service and control channels in time and frequency This research work focuses on the scalability of VANETs deployment, supported by WAVE protocol, both in sparse and dense network environments. Research work presented in [5, 7, 12, 13 and 11] addresses many factors that affecting the network scalability such as: 1. Number of admitted nodes to the network per lane, 2. High mobility of network nodes causing frequent handoffs with large overhead due to network association/re-association procedures, and 3. Number of broadcasting safety messages: timing and relevance of safety messages to the receiving vehicle based on its location and driving direction are vital factors in improving the network scalability and reducing unnecessary broadcast traffic. However, comparing the performance of VANETs deployment based onIEEE802.11P and the IEEEE 802.11P coupled with multi-channels support is notcovered in the literature. Therefore, the objectives of this research work are to: 1. Understand and apply simulation techniques to IEEE802.11P based VANETs networks, 2. Investigate why the existing MAC of 802.11P is not suitable for modern VANET deployment, 3. Investigate the suitability of using IEEE802.11p coupled with multi-channel extension (WAVE standard) as an alternative for the current VANET’s MAC layer and how this choice may affect the network scalability characteristic. The remainder of the paper is organized as follows. Section 2 introduces the simulation environment and parameters. Section 3 describes and summarizes the conducted experiments and simulation results. Section 4 concludes the paper and outlines future work. Frequency (GHZ) 5.925 SCH SCH 5.915 SCH SCH 5.905 SCH SCH 5.885 CCH CCH CCH CCH 5.875 SCH SCH 5.865 SCH SCH 5.855 SCH SCH CCH Interval SCH Interval CCH Interval SCH Interval Time Frame Interval Frame Interval
  4. 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 550 2. SIMULATION EXPERIMENTS 2.1.Simulation Engine Tool In this study, the NCTUns (National Chiao Tung University Network Simulator) is used. NCTUNs provides a coupled network and traffic simulator. By using a coupled model of simulation, any changes in the traffic status is communicated to the network simulation and an immediate feedback is sent back to alert vehicles on congested roads and possible lane changes. The NCTUns simulation uses a novel kernel reentering methodology for carrying on the simulation task and it is built on top of the Linux TCP/IP protocol stack for packet passes [14, 15]. Figure 3 shows the architecture of the NCTUNs simulation platform. The NCTUNs architecture consists of four major components: GUI, SE, Car Agent(s), and Signal Agent(s). These components play a major role in conducting the simulation task such as described below. Component #1: GUI (Graphic User Interface) The GUI provides users with the ability to construct different road network structures such as road segments intersection, traffic signal and number of lanes per road segment. Once the road network is ready, user can deploy the desired communication network technology and topology. At this point the GUI will automatically generate all configuration files for the other components. The GUI allows users to play back an animated session of packet transmission and vehicles movement, which helps in troubleshooting and ensure correctness of network protocol implementation. Component #2: SE (Simulation Engine) The SE is the coordinator among car and signal agents. SE is responsible for communicating requests/responses messages among these agents as well as simulating transport-layer and network-layer protocols. Component #3: Car Agent A car agent runs on each vehicle and composed of four sub-components: i. agent logic: controls driver behaviors based on the road conditions ii. road map database: supplies the shape/location of the road network iii. socket interfaces: provides an interface layer between TCP/UDP layer and the layers below to exchange application messages and road network information iv. car/signal information APIs: these APIs are used to allow the agent logic access to the car/road/signal information. Component #4: Signal Agent (SA) The signal agent runs on each crossroad intersection. SA controls the changing of the signal state of the four traffic lights located at the crossroad intersection.
  5. 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 551 Figure 3 The NCTUNs integrated platform architecture. Figure based in [14] NCTUns supports various ITS VANET standards such as IEEE 802.11 (a), (b) and (p). Moreover, NCTUns supports different realistic road network constructions such as highways, city streets and importing real road maps to study vehicles behavior in specific area. More information about NCTUns simulator can be found in [1, 2, and 14]. Accurate simulation results depend on using realistic vehicular environment including vehicles mobility patterns (highways as opposed to city streets), vehicles speed, and immediate response to changes in road conditions [1, 2 and 14]. For this simulation study, roads network are constructed using GVSU main campus roads structure such as shown in fig 4. Figure 4 Simulation Environment Road Map DB Agent Logic Socket Interface Car/SignalInf o APIs TCP Car Info DB Signal Info DB Car Agent GUI Protocol Stacks TCP/ UDP SignalInfo APIs Agent Logic Signal Agent TCPTCP TCP/ UDP TCP SE Signal AgentCar Agent
  6. 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 552 2.2.Simulation Experiments Setup Parameters Simulation experiments are carried out with different number of vehicles nodes (experiment- 1: 10 vehicle nodes, experiment-2: 20 vehicle nodes and experiment-3: 30 vehicle nodes). Vehicles nodes are randomly distributed in the road network structure. Fixed and mobile VANETs nodes are exchanging bacon signals that carry safety messages. The experiments are performed using the vehicular 802.11P MAC and 802.11P MAC with multi-channel extension support. Simulation parameters are collected to measure network throughput and determine how effective is each MAC type and its impact on the network scalability design characteristic [4 and 5]. In each simulation scenario, the experiments are conducted for 400 seconds in a 20 main road segments. Vehicles agents will use the Intelligent Driver Model (IDM), namely, Car Following Mobility model that controls the vehicles’ speed and direction. Also, IDM accounts for the presence of nearby vehicles when adjusting their moving speed to avoid collision with the front car. Vehicles are moving through the road structure with maximum speed of 25 m/s. 3. SIMULATION EXPERIMENTS RESULTS 3.1. Simulation Experiments Results (1)- Vehicular MAC 802.11P Figure 5 shows the network throughput under various network loads for 802.11P MAC. The network throughput is significantly affected by admitting new nodes into the network. Throughput has dropped from 6.0Mbps to close to 1.0 Mbps in the three scenarios. This drop in throughput is resulted from the MAC requirement of the 802.11P of having vehicles nodes send out probe requests and an association request. Now, the vehicle node associates with the network and starts to receive the safety alert messages. It is worth mentioning here that the time axis shows the performance metrics up to 100 seconds. The reason for this is I found no change in the network performance metrics values after 100 seconds. (a)10 Vehicle nodes in the field with 1-BS(b) (b)20 Vehicle nodes in the field with 2-BS (c) 30 Vehicle nodes in the field with 3-BS Figure 5 Network throughput with various vehicle nodes in the field (802.11P)
  7. 7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 553 3.2.Simulation Experiment Results (2)- Vehicular MAC 802.11P with multi-channel extension support (WAVE Standard) In this section, the VANET network is running 802.11P coupled with multi-channel extension support. Therefore, all OBUs and RSUs are using the same channel. Figure 6 shows the network throughput under various network loads. In comparison with the experimentation results (1), the network throughput is significantly improved tremendously. It appears that the WAVE standard does not use consume network resources by allowing vehicle nodes to join the VANET network and then receive safety messages. In another way, there is no probe request/response or association request/response. This process saves the network bandwidth and utilizes it efficiently in transmitting safety messages. (a) 10 Vehicle nodes in the field with 1-RSU (b) 20 Vehicle nodes in the field with 2-RSUs (c) 30 Vehicle nodes in the field with 3-RSUs Figure 6 Network throughput with various vehicle nodes in the field (802.11P with multi-channels extension) 4. CONCLUSIONS The presented work contributed to the following areas, (i) learning about different simulation techniques especially the new methodology of Kernel re-entering technique and how to apply it to VANETs networks and (ii) build realistic simulation scenarios and observe the VANETs network performance under various load conditions and different MAC technologies such as 802.11P and 802.11P with multi-channel support. Therefore, the use of 802.11P coupled with the multi-channel support would support the network scalability design criterion. In the future, further consideration to message authentication technique will be given to protect against broadcasting fake or false safety messages in VANET networks.
  8. 8. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 554 5. REFERENCES 1. S.Y. Wang, and Y.M. Huang (2012), “ NCTUns Distributed Network Emulator,” Internet Journal, Vol. 4, Num. 2, pp. 61-94, Nova Science Publisher (ISSN 1937-3805), 2012" 2. S.Y. Wang, P.F. Wang, Y.W. Li, and L.C. Lau (2011), “Design and Implementation of A More Realistic Radio Propagation Model for Wireless Vehicular Networks over the NCTUns Network Simulator,” IEEE WCNC 2011 (Wireless Communications and Networking Conference 2011), March 28 – 31, 2011, Cancun, Mexico." 3. Y. Zang, L. Stibor, B. Walke, H-J. Reumerman and A. Barroso (2007), “A Novel MAC Protocol for Throughput Sensitive Applications in Vehicular Environments”. Proc. of IEEE VTC2007-Spring, 22-25 April 2007, pp. 2580-2584." 4. V. Namboodiri and L. Gao (2007), “Prediction based routing for vehicular ad hoc networks”, IEEE Transactionson Vehicular Technology, Vol. 56, No. 4, pp.1-29. July 2007. 5. Ababneh, Nedal Labiod, Houda, (2010), "A performance Analysis of V ANETs Routing Protocols Using Different Mobility Models", IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS) 6. S.Y. WangCorresponding and C.L. Choua (2009),“NCTUns tool for wireless vehicular communication network researches”. Elsevier Simulation Modelling Practice and Theory. Volume 17, Issue 7, August 2009, Pages 1211-1226." 7. Yue Liu; Jun Bi; Ju Yang (2009),“Research on Vehicular Ad Hoc Networks”. Control and Decision Conference, 2009. CCDC '09. 17-19 June 2009 Page(s):4430 – 4435. 8. Dikaiakos, M.D.; Florides, A.; Nadeem, T.; Iftode, L.(2007), “Location-Aware Services over Vehicular Ad-Hoc Networks using Car-to-Car Communication”, Selected Areas in Communications, IEEE Journal onVolume 25, Issue 8, Oct. 2007 Page(s):1590 – 1602" 9. Fiore, M.; Harri, J.; Filali, F.Bonnet, C.;Politecnico di Torino (2007),"Vehicular Mobility Simulation for VANETs", 40th Annual Simulation Symposium,. ANSS '07. 10. Yunpeng Zang, Erik Weiss, Lothar Stibor, Bernhard Walke, Hui Chen and Xi Cheng (2008),“Opportunistic wireless internet access in vehicular environments using enhanced WAVE devices”, RWTH Aachen university. International journal of hybrid information technology, vol. 1, no. 2, April 2008." 11. Zang, Yunpeng and Stibor, Lothar and Walke, Bernhard and Reumerman, Hans-Juergen and Barroso, Andre (2007), "A Novel MAC Protocol for Throughput Sensitive Applications in Vehicular Environments". Proceedings of IEEE 65th Vehicular Technology Conference VTC2007-Spring, p. 5, Dublin, Irland, 2007. 12. Cristina Cocho (2009), "Analysis and Development of TDMA Based Communication Scheme for Car-to-Car and Car-to-Infrastructure Communication Based on IEEE802.11p and IEEE1609 WAVE Standards", Thesis performed in department of Programm und Systementwicklung of Siemens Österreich. 13. Y. Wang, H.L. Chao, K.C. Liu, T.W. He, C.C. Lin, C.L. Chou (2008), “Evaluating and improving the TCP/UDP performances of IEEE 802.11(p)/1609 networks”, IEEE Symposium on Computers and Communications 2008, Marrakech, Morocco, July 6–9, 2008. 14. Wang, S.Y.; Chou, C.L.; Chiu, Y.H.; Tzeng, Y.S.; Hsu, M.S.; Cheng, Y.W.; Liu, W.L.; Ho, T.W.; Nat. Chiao Tung Univ., Hsinchu, (2007), "NCTUns 4.0: An Integrated Simulation Platform for Vehicular Traffic, Communication, and Network Researches", The 66th IEEE Vehicular Technology Conference, VTC-2007 15. S.Y. Wang, Y.W. Cheng, C.C. Lin, W.J. Hong, T.W. He (2008), “A vehicle collision warning system employing vehicle-to-infrastructure communications”, Wireless Communications and Networking Conference 2008, Las Vegas, USA, March 31–April 3, 2008.
  9. 9. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976- 6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME 555 AUTHOR DETAIL Mostafa El-Said has received the M.S. and Ph.D. in Computer Science and Engineering from University of Louisville in 2000 and 2003 respectively. Dr. El-Said’s research interests include designing Smart Autonomic VoIP and VANET Systems. He is a member of the IEEE, and has served as a Vice-Chair of the IEEE Computer Society Technical Committee on Simulation (TCSIM) since 2005.Also, he is currently a member of the international programme committee and a reviewer for IEEE SmartGridComm, IEEE CCNC, SIMUTools, CGAMES and IJIGS. Dr. El- Said joined the faculty in The Pennsylvania State University, Information Sciences and Technology (IST) School in 2003. Since 2004, he has been with the Grand Valley State University (GVSU), where he is currently an Associate Professor in the School of Computing and Information Systems and Chair of the Information System Program. He is the founder and the director of the Wireless Systems Lab and the director of the Data Communication Center in GVSU.