, pp.80-84 http://dx.doi.org/10.14257/astl.2014.64.20 Optimized Vehicular Traffic Flow Strategy using Content Centric Network based Azimuth Routing ByungKwan Lee 1, EunHee Jeong 2 1 Department of Computer, College of Engineering, Catholic Kwandong University, Gangneung-si, Gangwon-do 210-701, Korea 2 Department of Regional Economics, College of Humanities & Social Sciences, Kangwon National University, Samcheock-si, Gangwon-do 245-711, Korea bklee@cku.ac.kr, jeongeh@kangwon.ac.kr Abstract. This paper proposes the Optimized Vehicular Traffic Flow Strategy (OVTFS) using Content Centric Network based Azimuth Routing (CCNAR). First, it measures the road condition in order to computes a risk for the efficient vehicular traffic flow. Second, it also proposes the CCNAR so that it may transfer accurately and rapidly to destination the traffic information message in which the computed risk is reflected. Compared to the existing CCN and AODV, the CCNAR diminishes the transmission times of request messages by azimuth and transfers it rapidly after receiving the traffic information stored in the Content Store (CS) of an intermediate vehicle. Keywords: Optimized Vehicular Traffic Flow Strategy, Azimuth Routing based on Content Centric Network 1 Introduction Electronic devices are downsizing and coming with wireless communication functions with the advancement of electronics technology, and various network structures are appearing to provide a variety of wireless services. In 2004, that Blum [1] began to carry out research on MANET was an opportunity of Vehicular Ad hoc Networks (VANETs) research [2]. This paper proposes the Optimized Vehicular Traffic Flow Strategy (OVTFS) using Content Centric Network based Azimuth Routing (CCNAR). Because the CCNAR reduces request messages by using azimuth, it can transfers traffic information rapidly. Also, the OVTFS prevents traffic jam or traffic accident from happening by separating the transmission zones of traffic information. 2 Content-Centric Networking 1 First author: ByungKwan Lee, Catholic Kwandong University 2 Corresponding author : EunHee Jeong, Kangwon National University ISSN: 2287-1233 ASTL Copyright 2014 SERSC
Content-Centric Networking (CCN) is a new paradigm recently proposed by PARC [3] aiming at rethinking the network architecture with a fundamental shift from an endto-end to a content-centric communication model. This approach is designed to deal with today s trends and proposes a unified, direct way to solve the aforementioned issues. In fact, CCN brings significant advantages, ranging from enhanced security to simplified network management. In addition, the generalized in-network caching is a key factor for realizing real economies by avoiding repeated transmissions of duplicated data over the same paths [4][5]. 3 Optimized Vehicular Traffic Flow Strategy 3.1 CCNAR Design 3.1.1 CCNAR Node Design In Fig.1, the CCNAR node is made up of Face, CS (Content Store), PIT (Pending Interest Table), FIB (Forwarding Information Base), and FAT (Face Azimuth Table). Fig.1. The structure of a CCNAR node The Face is identified with Sequence Number, the sequence number of the Face corresponds to the number of the neighboring nodes, and Interest packets and Data packets are input and output through the Faces. The CCNAR node collects neighboring nodes information using a Hello Packet and stores in the FAT the azimuth which is computed with the collected GPS information from the neighboring nodes. The CCNAR node confirms whether Data packet exists in CS if Interest packet arrives through the Face. If it exists, it is transferred to the nodes that requested data. If it does not exist in the CS, the CCNAR node stores in PIT the node identification that transmitted Interest Packet and requests a data packet to the neighboring nodes. At this time, the CCNAR node stores in FIB the neighboring node identification that requested data packet. Copyright 2014 SERSC 81
3.1.2 CCNAR Hello Packet Design The CCNAR node collects the information about neighboring nodes and manages it. When the Hello Packet message shown in Table 1 is used so that an CCNAR node can periodically transfer its information to neighboring nodes by the 1 hop, the GPS information field with location information and the RSU ID field with RSU ID are added to the existing Hello Packet. 3.1.3. Azimuth Measurement The OVTFA proposes the azimuth to reduce the transmission times of unnecessary messages. The CCNAR node receives Hello Packet from its neighboring nodes. There is the location information of the CCNAR node in the GPS information field of Hello Packet. The CCNAR node computes the azimuth using its location information and its neighboring nodes location information and stores the result in the FAT of the CCNAR node. 3.1.4. Caching of the CCNAR Node The CCNAR can update the data of the CS, the PIT, the FIB, and the FAT by using the fact that the RSU is changed because of the mobility of the CCNAR node. Table 1. The CCNAR s Hello Packet Message Type R A Reserved Prefix Size Hop Count Node IP Address Sequence number of node ALLOWED_HELLO_LOSS * HELLO_INTERVAL GPS information RSU ID Table 2. Traffic Information Message Field Contents Timestamp Message generation time RSU ID RSU ID generating a message Sequence Number Sequence Number of a Message Density road density Deceleration ratio reduction ratio of speed Node_X X coordinate Node_Y Y coordinate RSU_hop Message transmission scope according to risk 3.2 Transmission Strategy based on CCNAR In this paper, the RSU computes road risk by using several road conditions and generates a traffic information message of Table 2 according to the road risk and transfers this message to the CCNAR nodes and the neighboring RSUs. Algorithm 1. Road Risk Computation and Transmission Strategy 1: Check weather of road. if weather.information=ice then W=100 else if weather.information=fog then W=90 else if weather.information=rain then W=70 else if weather.information=sun then W=40 82 Copyright 2014 SERSC
2: Check congestion of road if congestion.information=0 then C=10 else if congestion.information=1 then C=30 else if congestion.information=2 then C=50 3: Check limitation of road. if limitation.information=yes then L=30 else L=0 4: Compute risk=w+c+l and set deceleration ratio. if (risk>=80 and risk<=100) then deceleration_ratio = 20% else if (risk >=110 and risk<=130) then deceleration_ratio = 30% else if (risk>=140 and risk<=150) then deceleration_ratio=40% else if (risk>150) then deceleration_ratio=50% 5: Set RSU_hop according to risk. if (risk<=80) then RSU_hop=1 else if (risk>=90 and risk<=130) then RSU_hop=2 else if (risk>=140) then RSU_hop=3 6: Generate Traffic Information Message and boadcast the message to neighboring RSUs until RSU_hop = 0. 4 Performance Analysis Like Fig.2, the number of messages generated by CCNAR, CCN, and AODV with 12 nodes are compared in the same environments. The CCNAR and CCN transfer data through Interest Message and Data Packet and the AODV transfers data through RREQ and RREP Message. For this experiment, nodes were arranged like Fig.2 and all the nodes obtained the information of the neighboring nodes within 1 hop. It is assumed that the node 3 requests traffic information and the node 12 has it. Fig.2. Broadcasting of a request message using azimuth The CCN and AODV search for all the paths bound for the node 12 by broadcasting Interest Message and RREQ Message separately to all the neighboring nodes. Contrary to the CCN and AODV, the CCNAR transfers Interest Message after reducing the broadcasting scope like Fig.2 by using the azimuth of the neighboring nodes. Therefore, because the CCNAR does not transfer messages to the opposite vehicles or the vehicles at the rear, it reduces network overhead and channel usage by Copyright 2014 SERSC 83
minimizing unnecessary message transmission. Table 3 shows the number of messages that the node3 transferred so that it might request data to the node12. Table 3 shows the number of messages that the node1 transferred so that it might request data to the node12 Table 3. The number of transferred messages Route Routing Protocol RREQ AODV CCN CCNAR RREP Interest packet Data Packet Interest packet Data Packet Case 1(node3 node12) 37 4 37 4 9 4 Case 2(node1 node12) 5 5 1 1 1 1 5 Conclusion This paper proposes the Optimized Vehicular Traffic Flow Strategy (OVTFS) using Content Centric Network based Azimuth Routing (CCNAR). The OVTFS has the following characteristics. First, the RSU generates traffic information messages considering road conditions and transfers them by using the CCNAR. Second, the CCNAR using azimuth not only diminishes network overhead by reducing traffic information request and response message but also transfers traffic information rapidly and accurately. Third, the OVTFS transfers traffic information to the neighboring RSUs more accurately. Acknowledgement. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2062415) References 1. Blum, J.J., Eskandarian, A., Hoffman, L.J.: Challenges of inter vehicle ad hoc networks. Intelligent IEEE Transactions on Transportation Systems, vol.5, no.4, pp. 347--351 (2004) 2. Kim, S.I., Kahng, H.K., Cheung, S.W.: Robust Route Establishment and Management for Vehicular Ad hoc Networks. Journal of KIISE, vol.40, no.1, pp.44--51 (2013) 3. Jacobson, V., Smetters, D.K., Thornton, J.D., Plass, M.F., Briggs, N.H., Braynard, R.L.: Networking named content. In Proc. of ACM CoNEXT 09. pp.1--12, Rome, Italy, 1-4 December (2009) 4. Smetters, D., Jacobson, V.: Securing network content. PARC Technical Report (2009) https://www.parc.com/ content/attachments/securing-network-content-tr.pdf 5. Carofiglio, G., Gehlen, V., Perino, D.: Experimental Evaluation of Memory Management in Content-Centric Networking. In Proc. of IEEE ICC, Kyoto, Japan, 5-9 June (2011) http://diegoperino.com/publications/ccn_ ICC11.pdf 84 Copyright 2014 SERSC