Infrastructure-Aid Information Forwarding Based on Network Coding in Vehicular Ad Hoc Networks Gang Wang, Yi Xu, and Xia Dai School of Electronics and Information Engineering, Beihang University, Beijing, China
[email protected]
Abstract. In this paper, we present an analytical study for data dissemination in vehicular ad hoc networks (VANET) in the urban areas. Without any routing protocol, random linear network coding (RLNC) is an efficient method in practical scenarios contrasted with flooding. In such scenarios, some vehicles cannot communicate with others due to their mobility and non-connection with the neighbors. To tackle this problem, we propose a mechanism using the roadside infrastructure to assist transmission, which allows the majority of vehicles in a connected domain. Through this mechanism, the packets delivery ratio is improved significantly and other properties are minimally affected. Furthermore, the feasibility of this approach is verified through the simulations. Keywords: Infrastructure-aid, information forwarding, network coding, vehicular ad hoc networks, urban area.
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Introduction
Intelligent Transportation System (ITS) is developed all over the world to settle the urban traffic management problems such as traffic jam, emergency treatment and vehicle route planning due to a surge of the vehicles number on the road. ITS is mainly applied in the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) to provide the traffic information about road obstruction, emergency incident, location and entertainment. Owing to the vehicle mobility, topographic conditions and traffic jam, more efficient wireless technique which can solve those problems to improve communication performance attracts significant interest from research communities[1-2]. In VANET, the vehicle speed is different in the urban scene and in the highway. In this paper, we focus on the urban scene. To ensure the efficient operations of the urban traffic, save driving time and reduce driving risk, the vehicular networks need to enhance the broadcast capacity, assure the transmission quality and share the traffic information immediately and efficiently. The remainder of paper is organized as follows. Section II provides a review of related works. In Section III, it proposes an infrastructure-aid forwarding mechanism based on network coding and provides the specific steps. In Section IV, we present the simulation results and finally Section V concludes this paper. Y. Wu (Ed.): Software Engineering and Knowledge Engineering: Vol. 2, AISC 115, pp. 557–565. © Springer-Verlag Berlin Heidelberg 2012 springerlink.com
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Related Works
Flooding is the simplest data dissemination protocol in mobile ad hoc networks [3]. The information can almost be transmitted to each node in the network. However, there still exist problems as follows: Firstly, due to the omnidirection of wireless transmission, most parts of the area are within multiple nodes transmission range, which result in broadcast storm for too much redundant information received. Secondly, the use of that mode may suffer from a high number of collisions and channel competition because the transmission time slots between adjacent nodes are highly correlated. Thirdly, abundant hidden and exposed nodes affect the reliability of broadcast information distribution. VANET has two primary applications: (1) Safe driving application. This application can significantly reduce the number of traffic accidents. According to the research, if the driver has half a second before the collision to be alert, then 60% of the traffic accidents will not happen; (2) User application. User application can give passengers advertising, entertainment and other information in the journey. For the first application, the alarms spread to each other inter-vehicles. Researchers have proposed some routing protocols such as the improved on-demand routing protocols and the improved geographic-based routing protocols. However, some protocols rely on the priori knowledge such as GPS positioning. In the actual VANET, the popularization of GPS is a process. So the robustness of the protocol should be considered. TIBCRPH [4] is a traffic infrastructure based cluster routing protocol. It also uses GPS to perceive the position. The maintenance of cluster-head will increase the protocol overhead. And some protocols ignore a lot of practical factors. For example, in most experiments all the vehicles are supposed to move at the same and constant speed. What is more, in different parts of the area, the density of vehicles are uneven, which factor is often ignored. For the second application, both vehicles and infrastructures can push the information to the other vehicles. Many routing protocols model P2P applications as BitTorrent to download multimedia files cooperatively [5]. In this application, most of the protocols only concern the case that only one large data source such as a multimedia file. CodeOn [6] uses Access Point to broadcast two kinds of messages unless the vehicles are outside the AP coverage. This paper focuses on the safe driving application. The main characteristic of such applications is that some of the data sources will send traffic information simultaneously and the size of the message is small. To avoid hidden terminal problem and increase the reliability in broadcast mode, several schemes such as transmitting RTB/CTB and acknowledgement messages [7] have been put forward. However, since the small safety message size is comparable to the RTB/CTB and acknowledgement message size, it would not be a reasonable choice in this application. Our ultimate goal is to propose a mechanism to improve network performance in the urban scene for safe driving application.
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Network Coding and Infrastructure-Aid Mechanism
We consider the random network coding schemes of [8] for all-to-all data transmission. The coding arithmetic exploited here is random linear network coding. Each source node that wants to transmit information to all other nodes (broadcasting packets) is independent of any routing protocols and has no data retransmission mechanisms. Nodes exchange coded frames instead of data packets. We define a coded frame c to be a linear combination of packet pk. n
c = ∑ ek pk
(1)
k =1
Where e denotes the coefficient of encoding packets in the finite Galois Field GF(q) with q = 28. In the header of a coded frame, the encoding vector e = [e1 ... en] is stored for the purpose of later decoding. When a node receives an innovative encoded packet, it will recombine the packets of its buffer and update the encoding vector e’ = [e’1 ... e’n] in the packet header: n
c ' = ∑ e 'k c k k =1
(2) .
Then continue to transmit until the coefficient vectors matrix E has a full rank in the buffers of all its neighbor nodes within its receiving range. Then the node starts to decode the packets after the packets coefficient matrix E reaches full rank. Then we can get the original packets through E and C.
P = E -1C .
(3)
In the urban area, some vehicles may have no neighbor nodes within the communication range in a certain time. Under that circumstance, we can utilize the roadside infrastructure such as road lamps, signal lamps to assist packets transmission. V2I communications and I2V can be applied to achieve V2V communication among unconnected vehicles, which makes more vehicles be aware of their surrounding road conditions, traffic accidents and other related information in a certain range. Infrastructure is characterized by high energy and wide transmission range. In this paper, infrastructure is employed only to store and forward data without recoding. Similarly, each node including infrastructure and vehicle which just broadcasts or encodes packets does not rely on any routing protocols and has no data retransmission mechanisms. To avoid collisions, each node sends packets with a random delay from 0 to 0.1s. Our mechanism is presented as the following steps: 1) We set five wireless base-stations uniform distribution. The base-station can receive signals from at least one other base-station. Its sending range is 330m that the vehicles can receive the signals sending by base-stations from 330m away. And the receiving range is 250m the same as the vehicles. 2) Each vehicle node sends to the network a single original packet and wants to collect all the other transmitted packets.
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3) The base-station forwards the packet it received to assist the node which has no neighbor node in its transmitting range. 4) Each original packet is sent only once. 5) When a node receives a linear independent packet, it reassembles the packets in the buffer and forwards the combination until the coefficient matrix of each neighbor has a full rank or the timer expires.
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Simulations
In this section, we discuss the relevant results via ns2 simulations. We adopt the basic MAC protocol IEEE 802.11b that, in the broadcast mode, does not use any acknowledgment mechanism. In case of collision, no retransmission occurs and the packet is lost.
Fig. 1. A street map in the urban scene
Network Topologies: There are some widely used mobility models such as Random Waypoint (RWP) to restrict the areas where nodes can appear. However, those models cannot reflect the real situation of the roads in the city scene. Here, we use the simulator VanetMobiSim to simulate realistic urban scene. In the simulation area: 30% are road-intensive areas; 30% are the residential areas; and the last 40% have sparse vehicles such as inside the hospital, park and playground. In order to be more close to the city scene, it selects at most six of the crossroads to set traffic lights. Vehicles must appear in the road following the traffic laws. Their speed is time varied between 20km/h to 50km/h and the vehicle will stop when the traffic light is red. One of the simulation scenarios is shown in Figure 1, a street map of 1,000m×1,000m in the urban scene. We test the algorithms varying the number of vehicles, n, from 20 to 60. Their speed is time varied between 20km/h to 50km/h.
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NC_I (Network Coding Infrastructure aid mechanism) and flood_I (Flooding Infrastructure aid mechanism) are the infrastructure-aid mechanisms respectively deriving from NC and flood. It sets five infrastructures in each scenario in the infrastructure-aid mechanisms. Performance Metrics: Packet delivery ratio, average delay, protocol overhead and throughput. Packets Delivery Ratio Packets delivery ratio is defined as the ratio between the number of received (or successfully decoded) packets and the number of transmitting packets. PDR =
Rp Sp
or ( PDR =
Dc p SP
)
(4)
Fig. 2. Packets delivery ratio for the various number of vehicles
SP and RP denote the number of all the transmitted and received packets. Fig.2 is compared to the packets delivery ratio over the number of vehicles. As observed with four protocols, the ratio of network coding is high. The NC_I is the best performance due to the infrastructure-aid. Once the vehicles move outside the sending range of the other neighbors, the infrastructure is working for forwarding packets. It helps vehicles to transmit the packets or coding packets to the farther position. Thus the packets delivery ratio with infrastructure-aid is obviously improved. Average Delay In great majority of network application, the end-to-end delay is an important performance that people focus on.
D (i ) = DT (i ) − ST (i )
,
(5)
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Fig. 3. Average delay for the various number of vehicles
where D(i) denotes the transmitting delay of the Packet i. RT(i) and ST(i) respectively denote the receiving time and sending time of the packet i. In particular, when use the network coding scheme, the decoding time is included in the delay. Thus DNC(i) denotes the time between the first transmission of Packet i and its reception and then successfully decoding at the destination nodes. DNC (i ) = DNC T (i ) − ST (i )
.
(6)
Then, we utilize the average delay D as one of performance metrics where N denotes the number of packets.
D=
1 N
N
∑ D(i) i =1
(7) .
From Fig. 3, the average delay of NC_I is a little longer than NC. In the infrastructure aid mechanism, the base-station assists the isolated nodes to forward packets. It has more hops than the common mechanism that the delay has a little increased. NC and NC_I are both much better than flood and flood_I yet. Therefore, infrastructure-aid has little negative impact on this performance. Protocol Overhead Protocol overhead is defined as providing services to the application to be sent any additional protocol information. Here it is denoted by PO.
PO =
SP RCBR .
(8)
SP is the number of all the transmitted packets in MAC. RCBR is the number of received packet which type is CBR. (Specially, when using network coding, R denotes
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the successfully decoded packets.)With the same number of packets sending to the network, NC_I receives more effective coding packets. Therefore, its protocol overhead is lower than NC. The protocol overhead result is described in Fig.4.
Fig. 4. Protocol overhead for the various number of vehicles
Throughput The throughput (TH) of network is calculated as the total number of packets received (or decoded), divided by the number of time slots it took until the last packet was decoded.
Fig. 5. Throughput for the various number of vehicles
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TH (i ) =
TB(i ) − TB(1) RT (i ) − RT (1)
(9)
TB(i) is the number of all the transmitted data when the packet i is successfully received (or decoded ) at the destination nodes. RT(i) is the receiving(or decoding) time of the packet i. So TH(i) denotes the average throughput. It is depicted in Fig.5. Since the base-station nodes forwarding information for the vehicles nodes, the connective data sources increase. However, if multi-nodes request to forward messages simultaneously, there must be a collision at the base-station. The throughput is decreased slightly. The results may be due to more neighbor nodes waiting for the matrix full. With the increased number of vehicles in the network, the negative impact on throughput is less and less. By contrast with flood and flood_I, the results of NC and NC_I are both better.
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Conclusion
In this paper, we concentrated on the infrastructure-aid mechanism for vehicular ad hoc network in urban scene for safe driving application. First we discussed the impact of network coding based protocol. We identified potential problems due to the mobility and non-connectivity of vehicles. To solve this, we proposed the infrastructure-aid information forwarding mechanism. This mechanism improved the packets delivery delay obviously, reduced the protocol overhead and has little negative impact on other performances. The effectiveness of our scheme was demonstrated by simulations. Acknowledgment. This work is supported by the National Natural Science Foundation of China (Grant No.60972007), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No.60921001), and the National Basic Research Program of China (Grant No.2010CB731800).
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6. Li, M., Yang, Z., Lou, W.: CodeOn: Cooperative Popular Content Distribution for Vehicular Networks using Symbol Level Network Coding. IEEE Journal On Selected Areas In Communications 29(1), 223–235 (2011) 7. Korkmaz, G., Ekici, E., Ozguner, F., et al.: Urban multihop broadcast protocol for inter-vehicle communication systems. In: Proceedings of the 1st ACM International Workshop on Vehicular ad Hoc Networks, pp. 76–85 (2004) 8. Fragouli, C., Widmer, J., Boudec, J.-Y.L.: Efficient broadcasting using network coding. IEEE/ACM Trans. Networking 16(2), 450–463 (2008)
