LSGO: Link State aware Geographic Opportunistic routing protocol for VANETs
© Cai et al.; licensee Springer. 2014
Received: 28 February 2014
Accepted: 29 May 2014
Published: 17 June 2014
Robust and efficient data delivery in vehicular ad hoc networks (VANETs) with high mobility is a challenging issue due to dynamic topology changes and unstable wireless links. The opportunistic routing protocols can improve the reliability of routing by making full use of the broadcast characteristics and assist in data transmission through additional backup links. In this paper, we propose a Link State aware Geographic Opportunistic routing protocol (LSGO) which exploits a combination of geographic location and the link state information as the routing metric. The LSGO aims to improve the reliability of data transmission in a highly dynamic environment, which selects the forwarders and prioritizes them based on the vehicle’s geographic location and the link’s quality. We compare the performance of LSGO with GpsrJ + which removes the unnecessary stop at a junction and greedy traffic aware routing protocol (GyTAR) using network simulator ns-2. The simulation results show that it opens more nodes to participate in the opportunistic data forwarding and increases a connection’s throughput while using no more network capacity than traditional routing. In the simulation, compared with other two protocols, when the number of vehicles and the average vehicle velocity increase, LSGO’s packet dropping rate is reduced and the network throughput is improved.
KeywordsVANETs Geographic opportunistic routing Link state Priority schedule
Vehicular ad hoc networks (VANETs)  are first designed for safety applications; afterwards, a series of applications for increasing traffic efficiency and providing comfort to the vehicle’s passengers are proposed. The network layer has received the most attention when working on VANETs. As a result, abundant routing protocols in such a network with differing objectives and for various specific needs have been proposed .
Existing routing protocols of VANETs fall into two major categories: topology-based and geographic routing. Topology-based routing [3–5] uses the information about links that exist in the network to perform packet forwarding. Since link information changes in a regular basis, topology-based routing suffers from routing breaks, so this kind of routing protocols is not suitable for VANETs. Geographic routing [6–15] uses neighboring location information to perform packet forwarding. In this kind of routing protocols, nodes are unnecessary to maintain a topology map or exchange link state information or maintain established routes as they do in a conventional mobile ad hoc routing protocol. Therefore, geographic routing can better adapt to network size and topology changes.
Greedy forwarding is the most widely used strategy in geographic routing. The fundamental principle is that a node forwards its packet to its neighbor that is closest to the destination. But the forwarding strategy can fail if no neighbor is closer to the destination than the node itself, and through this way, we can get the next hop which is nearly located beyond the transmission range of the forwarder. In this case, the established link is unstable and the signal strength may be reduced, which may cause an increase of the packet dropping rate. As the packet is forwarded using this kind of links, the probability of packet transmission failure is great. So, it will spend more resources on retransmissions. As a result, the network throughput is declined and the end-to-end delay is prolonged.
To solve this problem, De Couto et al. proposed a new measure called the expected transmission count (ETX) , which is the predicted number of data transmissions required to send a packet over the source to the destination link, including retransmissions. The ETX is widely used in routing protocols for wireless multihop networks [17–20] since its goal is to find the paths with the higher throughput and the less expected total number of transmission . The difficulty in using ETX in VANETs is that ETX does not consider the highly dynamic network environment, so we modified the ETX in this paper.
Although greedy forwarding strategy makes the hop transmission to the greatest extent close to the destination, the link is very unstable, which is because the two nodes at both ends of the link are located at the boundary of each other’s communication range. So, another forwarding strategy opportunistic routing is proposed, which could improve the reliability of data transmission by making full use of the broadcast characteristics and assist in data transmission through additional backup links. It makes the packets have more opportunities to be received. In the existing opportunistic routing protocols, some take hop count as the routing metric, some pay more attention to the cost, some consider the distance to the destination to be the forwarding mechanism, and some care more about the energy. However, few of them take a combination of geographic location and the link state information into account. So, we proposed a Link State aware Geographic Opportunistic routing protocol (LSGO) which takes a combination of geographic location and the link state information as the forwarder selection mechanism. Firstly, we propose a candidate node set selection mechanism, which selects the forwarders based on the vehicle’s geographic location and the link’s quality. In our approach, the link’s quality is measured using the enhanced ETX metric. Secondly, we put forward a priority scheduling algorithm which prioritizes the forwarders by timer-based scheduling method. This routing protocol can greatly improve the packet delivery ratio, ensuring data transmission reliability under a highly dynamic environment.
The rest of the paper is organized as follows: In Section 2, we will review the related work and introduce our motivation. Section 3 will present the details in the proposed LSGO scheme. The performance evaluations of the proposed scheme are presented in Section 4. Finally, Section 5 concludes the article.
2. Related work
3. Link State aware Geographic Opportunistic routing protocol
We propose an opportunistic routing called Link State aware Geographic Opportunistic routing protocol (LSGO) which takes a combination of geographic location and the link state information as the forwarder selection mechanism. The protocol aims to ensure a highly dynamic network packet delivery rate and improve the reliability of data transmission. Besides, it also aims to reduce the number of transmissions (including retransmissions) and the transmission delay. The protocol mainly includes three parts, namely, the estimation of link quality, candidate node set selection mechanism, and priority scheduling algorithm.
3.1. The estimation of link quality
However, the ETX metric does not specifically consider the mobility in VANETs. In LSGO, we improve the ETX to adapt to the network that is highly dynamic. There are two major improvements: the measurement of the link transmission rate and the calculation of ETX.
The denominator is the number of Hello packets that should have been received during the window, and τ represents the broadcast interval of the Hello packet. Count (t0,t) is the number of Hello packets received during t - t0. As can be seen from the formula, there are three situations in terms of the difference between t - t0 and window w. (1) 0 < t - t0 < 1, in this case, the packet delivery rate is the number of Hello packets received from t0 to t. (2) 1 ≤ t - t0 < w, the packet delivery probability in this condition is the number of Hello packets received from t0 to t divided by the length of this period. (3) t - t0 ≥ w, in this situation, the calculation is the same as the calculation in the ETX metric.
3.2. Candidate node set selection mechanism
That is, for the current node, the nodes in the candidate node set are the first n neighbors nearest to the destination. In addition, the distances from these n nodes to the destination are less than S(t). Note that if the network is sparse, it may result in a situation in which those n nodes cannot satisfy the condition . At this time, only if the distance from the neighbor node to the destination is less than S(t), the neighbor node is the candidate node.
The sending node would record the candidate nodes’ IDs and their priority numbers in the packet header after it selected the candidate node set. Since the number of candidate nodes n is dynamic, the size of the packet header is changing with it. If the network environment is good, the link between any two nodes is relatively stable, so the value of n and the packet header is small, which means that the overhead is small. On the contrary, if n and the packet header are large, then the overhead is large, too. The priority scheduling algorithm will be introduced in the next section.
3.3. Priority scheduling algorithm
LSGO uses timer-based priority scheduling algorithm, in which the highest priority node sends the packet firstly. For other candidate nodes, if they hear a higher-priority node send a packet, they would not process the packet; if the timer expires and a higher-priority node is not transmitting, they would begin to send the packet. The timer-based scheduling algorithm is simple and easy to implement and has no additional control overhead. However, the disadvantage is that it would introduce waiting time, thereby increasing the end-to-end transmission delay. Another shortcoming is that it may cause duplicate packet transmission, because the nodes in the candidate node set may not hear each other. But in VANETs, the packet passes along roads, and the road width is far less than the transmission range; in addition, the nodes that are selected by the candidate node set selection mechanism are located on one side of the current node, so all candidate nodes could hear each other from the distance perspective and duplicate transmission exists rarely in VANETs. An efficient scheduling algorithm should minimize the waiting time, which can be achieved in two ways: firstly, by assigning node priorities correctly, so that the optimal forwarding node has the highest priority and the higher-priority node has a better forwarding advantage, thus increasing the probability of selecting a higher-priority node that forwards packets and reducing the number of failed transmission, and secondly, by setting a reasonable waiting time for each node, which makes the low-priority node forward packets immediately after the high-priority node failed, thereby reducing the waiting time between the candidate nodes.
D sd is the distance between the current node and the destination. D id is the distance from candidate node i to the destination node. ETX i is the ETX of the link that is formed by the current node and candidate node i. D sd - D id indicates the geographic distance a packet can advance towards the destination. However, due to link loss, to be successfully forwarded to node i, a packet needs to be transmitted ETX i times on average. Therefore, (D sd - D id ) / ETX i is the expected advance that a packet can make towards the destination through one transmission if it chooses node i as the next hop.
Passing by a link of low transmission rate will increase the probability of data transmission failure, so we divide the square of ETX in Equation 7. If candidate node i does not receive data correctly, another candidate node whose priority is lower than i will transmit the data, thus introducing additional waiting time. If two nodes have the same expected advance that a packet can make towards the destination through one transmission, the node whose ETX is smaller should be set a high priority.
The sending node will calculate each candidate node’s value according to Equation 7 as soon as it finishes selecting all the candidate nodes and assign priorities for candidate nodes in accordance with the calculation results. The node which has the maximum calculation result is assigned the highest priority; on the contrary, the node which has the minimum calculation result is assigned the lowest priority. The highest priority node sends a packet directly when it receives the packet, while the lower priority nodes need to set a timer. If the timer expires and a higher-priority node is not transmitting, they would begin to send the packet. Only by setting a reasonable overdue time for the timer can both reduce delay time and avoid duplication of transmission.
The network delay is defined as the time from a node receiving a packet to send it completely, and it consists of four parts: the processing delay, queuing delay, transmission delay, and propagation delay. Since we do not consider the network load, which means not considering the queuing delay, the network delay consists of three parts. Assuming that the total time of these three parts is T, if the node priority is i, the timer should be set to (i - 1)T. In our simulation, the packet size is set to 512 bytes. The protocol in MAC layer is 802.11, in which the channel rate is 2 Mbps. So, the transmission delay is equal to 512 × 8 bits / 2 Mbps = 0.002048 s. The radio wave propagation velocity in air is equal to the speed of light, namely, 3 × 108 m/s. However, the distance between two vehicles who can communicate with each other directly is less than 250 m. So, the propagation delay is equal to 250 m / 3 × 108 m/s = 0.83 × 10-6 s, and it can be ignored. Through doing multiple times of simulation and analyzing the trace files, we can get the processing delay which is approximately 0.001 ~ 0.002 s. Therefore, based on the above analysis, we can conclude that T is about 0.004 s.
4. Simulation results and evaluation
In this section, we study the performance of LSGO by running a computer simulation with network simulator ns-2 (version 2.34) . GPSR is the most fundamental and classic geographic routing protocol, and it first proposes the greedy forwarding strategy, which is the most widely used strategy in VANETs. In addition, GPSR is the basis for most of the geographic routing protocols and often used as the comparison protocol. But its recovery mode has a problem called Baby Step Problem. To solve this problem, GPCR is proposed. Packets are always greedily forwarded along the road from one junction to the other, which solves the Baby Step Problem in GPSR. However, even if a packet is forwarded along the street, it needs to stop at each junction node. GpsrJ +  removes the unnecessary stop at a junction while keeping the efficient planarity of topological maps, improving GPCR to better adapt to the VANETs in a city scenario. It manages to increase the packet delivery ratio of GPCR and reduces the number of hops in the recovery mode compared to GPSR. So, we choose GpsrJ + as one of the contrast protocols. The greedy traffic aware routing protocol (GyTAR)  improves the greedy strategy that tries to mimic the shortest path routing by taking into account the road connectivity. A score is given to each neighboring junction considering the traffic density and their distance to the destination. It is good at finding robust routing in a city environment. Since the scenario in our simulation is also an urban scenario, we take GyTAR as another comparison protocol.
4.1. Simulation settings
2,500 m × 1,500 m
Number of vehicles/vehicle velocity
100 ~ 200/10 ~ 20 m/s
Number of vehicles/vehicle velocity
100/9 ~ 24 m/s
IEEE 802.11 DCF
Number of CBR connections
Window size w
4.2. Results and analysis
In this paper, we put forward a new routing protocol for VANETs called Link State aware Geographic Opportunistic routing protocol (LSGO) which takes a combination of geographic location and the link state information as the forwarder selection mechanism. The protocol aims to ensure a highly dynamic network packet delivery rate and improve the reliability of data transmission. Besides, it also aims to reduce the number of transmissions (including retransmissions) and the transmission delay. LSGO uses an improved ETX mechanism to calculate the link transmission rate. The protocol is mainly composed of two parts: the candidate node set selection mechanism and the candidate node priority scheduling algorithm. To validate the performance of the protocol, we have compared it with GpsrJ + and GyTAR via ns-2. The simulation results showed that when the number of nodes changes, LSGO’s packet dropping rate is reduced by about 28% and 17%, and the network throughput is improved by about 42% and 22%. When there are 100 vehicles in the network and the average vehicle velocity increases, LSGO’s packet dropping rate is reduced by about 71.8% and 69.9%, and the network throughput is improved by about 187% and 123%. So, we can make a conclusion that LSGO achieves a higher throughput and lower packet dropping rate in highly dynamic networks. Although LSGO’s overhead is slightly larger than that of the other two protocols, we think that the cost of a little overhead in exchange for a higher delivery rate is reasonable.
In this paper, the theoretical analysis is less, and we only validate the performance of the protocol by simulation. So, in the future, we will do some theoretical analysis and further modify our routing protocol to reduce the overhead.
This work was supported by the National Natural Science Foundation of China under Grant No. 61271176 and No. 61231008, the National Science and Technology Major Project under Grant No. 2011ZX03001-007-01 and No. 2013ZX03004007-003, the Fundamental Research Funds for the Central Universities, and the 111 Project (B08038).
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