Preset delay broadcast: a protocol for fast information dissemination in vehicular ad hoc networks (VANETs)
© Gonzalez and Ramos. 2016
Received: 22 January 2016
Accepted: 16 April 2016
Published: 26 April 2016
Vehicular ad hoc networks (VANETs) have been proposed in order to assist the driver on the road. There are multiple applications where VANETs are needed, for example, proposing routes to reach a given destination, cooperating for traffic management, or preventing the driver of dangers on the road. In this paper, we focus on message broadcast for driver safety. Such broadcasting must be fast and reliable such that all the vehicles in a certain area receive the message as fast as possible. There are several proposals in the literature of broadcast protocols for critical messages in VANETs. In order to get a wide view of the different techniques to broadcast a message, we evaluate a set of protocols representing one or more broadcast techniques. Moreover, we propose PDB, a preset delay broadcast protocol with a fixed delay for vehicles attempting to retransmit a warning message, which provides a fast and reliable dissemination. We show that by adequately setting the waiting time for the relay candidates, we can significantly reduce the delay to cover a given area, while at the same time preserving a good reliability. Moreover, we model different techniques to broadcast an emergency packet in a VANET such as count-based, geographical, distance-based, and opportunistic, and thus we implement a subset of state-of-the-art protocols that implement one or more of those techniques. Finally, our research shows that stopping beacon transmissions when a warning message is detected does not provide a significant performance improvement. Nonetheless, by allowing a continuous channel access, we prove that the performance of any protocol might be greatly increased.
We focus mainly on the broadcast of messages for driver safety. Such a broadcast process must be fast and reliable such as all the vehicles in a certain area receive the message as fast as possible; however, two main problems may arise. On one hand, VANETs suffer from the broadcast storm problem occurring when all the vehicles or a large subset of them rebroadcast a packet. When this occurs, the medium access contention increases, which produces a high delay on message delivery, message collisions, and hidden terminals. On the other hand, VANETs also exhibit the network disconnection problem, which is due to the vehicles’ mobility that causes network partitioning and becomes eventually the cause for the loss of communication.
The rest of this paper is structured as follows. Section 2 reviews the related work about the proposed solutions for the broadcast storm and network disconnection problems. Section 3 describes the protocols we analyze in this work as well as the considerations we take to compare them. Then, we propose in Section 4 our preset delay broadcast (PDB) protocol that exhibits a fast message dissemination and a high reliability. Section 5 depicts the scenarios evaluated along with the implementation of state-of-the-art protocols in order to compare their performance with PDB. Next, we present in Section 6 the results we obtain after an extensive campaign of simulations. Finally, Section 7 sketches our conclusions and future work.
2 Related work
The research on VANETs currently covers a wide set of subjects, where among the most important ones we may find the work on routing protocols, multimedia services, multicast, and broadcast transmission. We provide below a brief overview of the state of the art on each of these directions in order to point out where our work is focused.
Regarding routing protocols, Spyropoulos et al.  identify a taxonomy of opportunistic protocols for delay-tolerant networks (DTNs). The aim of such work is to provide guidelines for designers so that one may choose a network routing protocol well suited for applications. The main identified relevant parameters for the routing process in that work are network density, node heterogeneity, and mobility patterns. In , the authors focus on energy saving and propose DRSS (directional routing and scheduling scheme), which is a routing protocol for DTNs that uses a Nash Q-learning approach to optimize energy efficiency along with network congestion, buffer, and delay occupation. The proposed scheme is implemented on the NS-2 simulator to show its ability to improve energy efficiency and data delivery ratio with such a learning mechanism to predict the network environment. Moreover, the work in  focuses also on energy-efficient protocols and proposes a data collection method that the authors call Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection (EDAL) protocol. The authors prove that the problem formulation is NP-hard. Even if EDAL is proposed for wireless sensor networks, the mechanism might be useful for different types of networks like VANETs.
Concerning multimedia services for VANETs, in , Zhou et al. propose a distributed media service to solve the trade-off among content dissemination, cache update, and fairness for P2P-based (peer-to-peer) vehicular networks. The proposal focuses on user satisfaction rather than on quality of service and considers media-aware distribution along with opportunistic transmission. Besides, the work in  provides a great overview of multimedia services for cloud-based VANETs. The main technological challenges of providing cloud-based services are discussed by considering communication infrastructure, cloud taxonomies, network integration, and a wide set of applications.
Considerable work has been done on multicast protocols for mobile ad hoc networks (MANETs). Protocols for MANETs may often be adapted to operate on VANETs, so contributions on this direction may be very useful to provide efficient multicast mechanisms for both types of networks. For example, in , the authors propose a multi-constrained QoS multicast protocol that uses a genetic algorithm. The proposed protocol therein takes into account parameters such as crossover, mutation, and population size. Also, in [13, 14], the authors propose CodePipe, which is a reliable multicast protocol designed to exhibit very good performance on energy efficiency, throughput, and fairness.
Cooperative road safety applications
Emergency electronic brake lights
Safety function out of normal condition warning
Emergency vehicle warning
Slow vehicle warning
Vulnerable road user warning
Wrong way driving warning
Stationary vehicle warning
Traffic condition warning
TLPMBonE, TLPMGonE, or AMTbyTME
Signal violation warning
TMBonE or AMTbyTME
TMBonE or TMGonE
Decentralized floating car data
1 to 10 Hz
Overtaking vehicle warning
Lane change assistance
Pre-crash sensing warning
Cooperative glare reduction
Across traffic turn collision risk warning
Merging traffic turn collision risk warning
Cooperative merging assistance
Hazardous location notification
TMBonE or AMTbyTME
Intersection collision warning
Cooperative forward collision warning
Collision risk warning from RSU
In this paper, our focus is on broadcast protocols for critical messages. Such protocols intend to solve at least one of the two main problems faced by VANETs, i.e., broadcast storm and network disconnection. Next, we summarize the main broadcast techniques for critical messages in the literature [16, 17]. Moreover, the main contribution of this work is our PDB protocol that provides a fast and reliable message dissemination. PDB is described later in Section 4.
When a vehicle receives a message for the first time, it must rebroadcast it. Therefore, each vehicle receiving a message for the first time must repeat this procedure until all the vehicles in a desired area receive the message. This type of broadcast exhibits high reliability in a sparse network. However, for dense networks, flooding may suffer from the broadcast storm problem. Furthermore, the collision probability increases as well as the hidden terminal problem. These algorithms are inspired on those used for mobile ad hoc networks, like the one in .
In this type of protocols, each vehicle that receives successfully the message decides whether to rebroadcast it or not according to a probability distribution. These protocols reduce the medium contention as well as the number of collisions and redundant messages. However, when these protocols are used in sparse networks, it is possible that some vehicles do not receive the message. The speed adaptive probabilistic flooding algorithm  and the weighted p-persistent, slotted 1-persistent, and the slotted p-persistent are examples of probabilistic protocols . In , an adaptive probabilistic protocol is proposed where, on one hand, vehicles in a dense network have a low probability of rebroadcasting messages and, on the other hand, in a sparse network they have a higher rebroadcast probability.
Vehicles in a VANET that implement this type of protocols decide to rebroadcast a message based on the number of times they have received the same message. The main idea is as follows: when a vehicle receives a message for the first time, it waits a time t before rebroadcasting it. When a vehicle receives the same message and exceeds a given threshold, then such a vehicle cancels the rebroadcasting process. Thus, if the timer expires, the vehicle does not rebroadcast the message since it has been rebroadcast for other vehicles. If the timer expires and the threshold has not been reached, then the vehicle must rebroadcast the message in order to increase the coverage of the message. This type of technique has been combined with the probabilistic scheme in , where the authors propose to rebroadcast a message according to a probabilistic distribution, while at the same time the protocol manages a counter to cancel the procedure if the message has been received too many times. Moreover, an adaptive counter-based protocol is proposed in . Here, nodes rebroadcast a message considering the number of times that the message is received along with the inter-arrival times. In , the authors propose a dynamic counter-based protocol. In this protocol, the authors use a different threshold depending on how many vehicles are close to the node. A node trying to rebroadcast a message that is within a dense area of vehicles will have a smaller threshold than when it is in a sparse area.
In this type of protocols, the decision of whether to rebroadcast a message or not depends on the distance between the transmitter and the receiver. Hence, only the vehicles located at a distance greater than a given threshold rebroadcast the message. These protocols are highly dependent on the threshold, which often causes a variable performance. In , the authors propose a protocol where the vehicles attempting to retransmit a message wait t seconds, where t depends on the distance between the transmitter and the receiver as well as on the communication range. In , a protocol that selects the relay by partitioning the communication range is proposed; here, the vehicle located in the farthest partition retransmits the message.
2.5 Neighbor knowledge
In order to decide whether to rebroadcast a packet or not, this type of protocols take advantage of the location and movement of the neighbors. Thus, a vehicle may decide if there is a better relay or if it is the best candidate. However, for sparse networks, this algorithm might lack the necessary information to make the best choice. In [27, 28], the authors make use of connected dominating sets (CDS) to propose a protocol aimed to reduce unnecessary retransmissions. With CDS, a graph is created in order to select the minimum number of nodes to cover 100 % of their corresponding neighbor nodes.
The main idea of opportunistic protocols is to take advantage of the opportunities inherent to the broadcast process. Thus, the farthest vehicle that receives successfully the message has more chances to rebroadcast the packet, hence the broadcast process may complete with few hops. In , the authors assign a high priority to the farthest vehicles so they have a shorter waiting time to rebroadcast the message. In , we extend and improve OB-VAN  where the farthest vehicles have more chances to rebroadcast the message. We adopt the OB-VAN’s main idea for the selection process. Once a vehicle receives a packet, intervals of the same length are generated to receive or transmit short acknowledgments. When a vehicle is within the reception interval and receives an acknowledgment, then such vehicle stops its corresponding selection process meaning that there is a better relay. The main difference between OB-VAN and our previous proposal, Fast-OB-VAN, is that the latter transmits the emergency packet rather than a short acknowledgment. Fast-OB-VAN achieves a faster message dissemination by carefully selecting what it sends.
3 Study cases
3.1 Protocols analyzed
In order to account with a general view of the different techniques to broadcast a message, we select a set of state-of-the-art protocols implementing one or more techniques listed above. Thus, we implement a simple flooding protocol since such a dissemination technique represents the worst case. In a similar way, we also implement a simple counter-based protocol with a threshold equal to three messages. Moreover, we implement the bounding algorithm originally proposed for MANETs , which uses the counter and distance techniques; the main motivation to implement this protocol is that it may potentially cover a given area with few hops. Regarding the neighbor knowledge approach, we implement the non-GPS data dissemination protocol , which uses the number of neighbors of each vehicle to decide which vehicle rebroadcasts a message and, ideally, covers all the vehicles. An additional feature of this protocol is that it does not require to know the vehicles’ location to select the best relay; thus, a Global Positioning System (GPS) is not needed. A GEographical Data Dissemination for Alert Information protocol gives an overview of the performance of geographical algorithms. Such a technique makes a partition of the communication range, which causes that only the vehicles in some partitions are able to retransmit the messages. We address opportunistic protocols with OppCast, which takes advantage of the distance between the transmitter and receiver. We also implement our previous contribution Fast-OB-VAN. As with OppCast, Fast-OB-VAN also uses the distance to select the best relay.
Finally, we evaluate the performance of our proposal that is discussed in Section 4.
3.2 Algorithm efficiency
3.3 Stopping beacons
3.4 Continuous access
4 Preset delay broadcast (PDB) protocol
Our goal in this work is to design a protocol that exhibits low delay and high reliability. Thus, we propose our PDB protocol with a fixed delay for vehicles attempting to retransmit a warning message in order to provide a fast message dissemination. The PDB protocol is fully compliant with the IEEE 802.11p standard. Thus, we guarantee an efficient message dissemination that closely follows the standard specifications. Moreover, we assume that all the vehicles are equipped with a GPS, and thus they are aware of their location. Such assumption is considered by most of the broadcast protocols for VANETs because WAVE systems require the exchange of this type of information.
In a WAVE system, all the vehicles share their location and movement by means of beacons. Accordingly, a vehicle needing to transmit a warning packet knows how far its neighbors are located. With such information, the source may sort the neighbors according to the distance. Therefore, the source may decide which neighbors are the best candidates to retransmit the message among the ten farthest ones. Thus, the farthest neighbors must have a lower delay to retransmit the packet. In this work, we set a delay of 0.5 ms for the farthest neighbor, 1 ms for the second farthest neighbor, 1.5 ms for the third farthest neighbor, and so on until the tenth farthest neighbor that has a delay of 5 ms. Hence, when a vehicle transmits a warning packet, the farthest ten neighbors are added to the warning packet. Additionally, the distance of the farthest neighbor is added too.
When a vehicle retransmits a warning message, it will replace the list of IDs with its corresponding list according to its neighbors. In addition, in order to deal with network disconnections, it is possible to implement the mechanism store-carry-forward as described in . Finally, when a vehicle receives the warning message for the second time, then it cancels the retransmission and ignores future receptions of that message. Algorithm 1 provides the pseudo-code of our proposed PDB protocol.
5 Simulation scenario and performance parameters
1.1 m/s 2
5.0 m/s 2
20 dB m
Propagation loss model
Constant speed propagation
SCH and CCH duration
Beacon generation rate
Emergency packet generation rate
1/10 s −1
In this section, we present the results we obtain after an extensive campaign of simulations. We focus on four parameters: the delay to cover a target area, the number of packet retransmissions, the number of vehicles having correctly received the broadcast packet within a certain area, and the number of times that the protocol completes correctly. For the first three parameters, the measurements are taken only when the protocols complete correctly.
6.1 Average delay
Protocol efficiency. For the first study case, flooding is the fastest protocol covering 1 km. This is because such a protocol does not have to deal with a waiting time to rebroadcast the message. Then, PDB and bounding closely exhibit delays similar to flooding. On one hand, since PDB presets a delay value, the waiting time to rebroadcast a packet is controlled, which allows to obtain a small delay. On the other hand, bounding allows at least three of the farthest vehicles to rebroadcast the packet. With a slightly higher delay, we find the count-based and NonGPSDD protocols exhibiting a similar behavior. However, notice how the delay of NonGPSDD decreases when vehicle density increases. Then, the protocols following in delay performance are Fast-OB-VAN, closely followed by GEDDAI and OppCast.
Stopping beacons. For the second study case, we stop beacon transmissions. There is a decrease on delay; however, it is quite small. Thus, it might be hard to see a difference between plots in Fig. 10 (top-left) with those in Fig. 10 (center-left). Hence, it is clear that stopping beacons does not contribute in a significant way to reduce the delay needed to cover a given area.
Continuous access. In our third study case, we allow vehicles to continuously access the channel. Thus, we may see in Fig. 10 (bottom-left) that all the algorithms exhibit a delay lower than the previous study cases. Such a decrease on the average delay is because the message does not have to wait for channel switching. Thus, the message is sent as soon as needed.
Hence, only taking into account delay, the best choice to broadcast a message is flooding, followed by our PDB protocol and bounding. The analysis we provide in the following subsections will show if such a behavior is preserved.
6.2 Packet retransmissions
In order to measure this parameter, we focus on the average number of vehicles rebroadcasting a packet. We consider that a given vehicle rebroadcasts a packet after a successful reception and the broadcast algorithm retransmits such packet. Furthermore, the packet retransmission rate is calculated by dividing the total number of vehicles retransmitting the packet by the total of number of vehicles successfully receiving it.
Protocol efficiency. We can see in Fig. 10 (top-right) that bounding is the protocol requiring the lower number of retransmissions. Then, Fast-OB-VAN, GEDDAI, NonGPSDD, and OppCast show a similar performance. These last algorithms along with PDB exhibit a similar performance for a low number of nodes. However, notice how the performance of PDB increases starting at 34 nodes; this is because we assign a lower waiting time to the relay candidates. Since the difference to rebroadcast the packet between vehicles is 0.5 ms, they cannot opportunely receive the packet and rebroadcast it. Nevertheless, when the vehicle density increases, the retransmission rate decreases, which is a desirable feature for all the algorithms. Then, we can see that starting with 17 nodes, the counter-based protocol incurs in a high rebroadcasting rate, then such a measure quickly decreases; however, notice that its performance slowly increases when vehicle density increases as well. Finally, with flooding, all the vehicles that successfully receive the packet must rebroadcast. Thus, we get a 100 % of the vehicles rebroadcasting the packet.
Stopping beacons. Similarly as it happens with the average delay, with our second study case that considers to stop beacons, the difference in performance is quite small; thus, Fig. 10 (top-right) and Fig. 10 (center-right) are similar. Hence, we can conclude again that stopping beacons does not contribute in a significant way to reduce the percentage of vehicles rebroadcasting a packet.
Continuous access. Our third study case considers continuous access to the channel. Thus, we may appreciate in Fig. 10 (bottom-right) a slight decrease on the percentage of vehicles rebroadcasting the packet. We can explain such a decrease with the fact that the broadcast process is not interrupted for channel switching.
6.3 Number of times the protocol completes correctly
We consider that the protocol completes correctly if the packet successfully arrives at a vehicle located at least 1 km away from the vehicle that created such packet. If no vehicle satisfies such condition, then we consider that the protocol does not complete correctly. With this information, we can determine how reliable the protocols are.
Stopping beacons. As what happens with previous cases, by comparing Fig. 11 (top-left) and Fig. 11 (center-left), we clearly see that stopping beacons does not significantly contribute to improve the percentage of times that the protocol completes correctly.
Continuous access. Figure 11 (bottom-left) shows a slight performance increase for most of the protocols. However, bounding has a drastic increase on reliability. This implies that channel switching highly impacts the performance of the bounding protocol. Nevertheless, bounding still has the worst reliability among the rest of the protocols.
6.4 Percentage of vehicles receiving the broadcast packet
The last parameter we consider in our evaluation is the average percentage of vehicles receiving the broadcast packet. This is calculated by dividing the number of vehicles that successfully receive the packet by the total number of vehicles in the area of interest.
Protocol efficiency. The first study case is plotted in Fig. 11 (top-right). Even if flooding exhibits a good performance in terms of delay as well as on the percentage of time that the protocol completes correctly, in this case, flooding shows a low percentage of vehicles receiving the broadcast packet when the vehicle density is low. In the same way, bounding shows a similar behavior when the vehicle density is low. The rest of the protocols show an excellent percentage of vehicles receiving the broadcast packet, which is above 97 %.
Stopping beacons. Unlike the previous parameters, notice in Fig. 11 (center-right) how the flooding protocol exhibits a performance increase. The rest of the protocols also show a small performance increase.
Continuous access. We can see in Fig. 11 (bottom-right) a performance improvement for the bounding protocol. For this study case, all the protocols reach more than 94 % of vehicles correctly receiving the broadcast packet.
In this work, we made an extensive analysis of several protocols proposed in the literature for message dissemination in VANETs under three study cases. In order to exhibit low delay and high reliability to broadcast warning messages, we proposed a protocol that sets the waiting time for relay candidates. We shown that by doing this, we can significantly reduce the delay needed to cover a given area. Furthermore, even if our PDB protocol incurs in several retransmissions, they are significantly reduced as the vehicle density increases. Additionally, PDB offers a high reception rate and high reliability when covering an interest area.
In order to model different techniques as count-based, geographical, distance-based, and opportunistic, we implemented a subset of protocols using one or more of such techniques. We may see that flooding provides the lowest delay to cover a given area. However, its message dissemination suffers from the broadcast storm problem since all the vehicles receiving the broadcast packet must retransmit it, and this reduces the reception rate because of collisions or hidden terminals. Bounding combines the count-based and distance-based techniques. In a vehicular environment, bounding exhibits a very low propagation delay with a few number of retransmissions. However, since such a protocol only allows to contend for being a relay among the vehicles within a certain area, it has success only very few times; i.e., it is unreliable. NonGPSDD is self-dependent from the use of a GPS; this is an advantage for VANETs. Even if this protocol shows good performance in general, the delay tends to quickly increase when the density of vehicles increases as well. The geographical protocol (GEDDAI) along with the opportunistic Fast-OB-VAN and OppCast perform well in most of the metrics considered. However, these protocols exhibit the highest delay to cover the area of interest. Finally, the counter-based and our proposed PDB protocol show similar performance. On one hand, one important difference is the percentage of vehicles rebroadcasting the packet; the counter-based protocol incurs on fewer retransmissions than PDB for most of the vehicle densities. Even so, the counter-based protocol tends to increase the number of retransmissions along with the density of vehicles, whereas PDB tends to decrease the number retransmissions with a higher density of vehicles. On the other hand, PDB exhibits lower delay than counter-based.
We have also shown that stopping the beacons when a warning message is detected does not represent a major performance improvement. However, allowing a continuous channel access is beneficial for all the protocols to a large extent.
As a future work, we will analyze the performance of our PDB protocol in a more complex scenario. Our main interest is to study the behavior of PDB on highways and urban areas, as well as with multiple sources generating emergency messages. The main motivation for doing so is to identify the performance difference when PDB is executed on a highway environment since the vehicle speed is normally faster than when vehicles move in an urban scenario. Also, for urban scenarios, vehicle density is greater than for highway scenarios. Furthermore, we would like to assess the performance of PDB under multiple warning message sources. With such an assessment, we will account with the necessary information to know if the protocol still exhibits good performance with a greater network load.
The authors are grateful to the National Council of Science and Technology (CONACyT: Consejo Nacional de Ciencia y Tecnología) for supporting this work.
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