CAGFP: Context Aware Geocast Forwarding Protocol

for Inter-Vehicle Communication

Himan Zarza, Hamid Karimi, Seyed Mohammad

Hosseini, Saleh Yousefi

Department of Computer Engineering

Urmia University

Urmia, Iran

{st_h.zarza, st_ha.karimi, st_m.hosseini,

s.yousefi}@urmia.ac.ir

Hamid Reza Ataeian, Habib Rostami

Department of Information Technology

ACECR-Sharif Branch

Tehran, Iran

{ataeian, hrostami}@jdsharif.ac.ir

Abstract— Timely and reliably informing the derivers about an

occurred danger on a roadway seems completely critical in

Intelligent Transportation Systems (ITS). Real-implementation

of IVG (Inter-vehicle Geocast) as a major algorithm in this field

reveals some failure due to clustering phenomena of vehicle

traffic. Therefore, in this paper, we propose CAGFP (Context

Aware Geocast Forwarding Protocol) which forwards safety

alarms for relevant section of the road. Based on IEEE 1609

standard, beacon safety messages are periodically disseminated

in the CCH (Control Channel). Therefore, in the proposed

algorithm we take advantage of the broadcasted beacons in

order to alleviate the problem of broadcast storm. Simulation

results show low delay, less re-broadcasts and higher reception rate compared to IVG algorithm.

Keywords—Vehicular communication; VANETs; Accident;

Forwarding.

I. INTRODUCTION

Accidents are most hazardous events facing the drives on the roads. Cause of most of the accidents is human mistakes. An occurred accident (or generally any other dangers) could be thwarted against other derivers if they would be notified about that event in advance. One of the vivid examples of these road events is chain accident wherein rear vehicles hit the front crashed one(s) which consequently brings about a chain of accidents.

One remedy of aforementioned scenario is inter-vehicle communication– wireless access in vehicular environments (WAVE) [1]. Recently there has been a lot of academic and industrial attentions toward WAVE. IEEE 802.11p is based on WAVE. In fact IEEE 802.11p plus IEEE 1609. 1/2/3/4 comprises inter-vehicle communication. IEEE 802.11p has been designed for highly mobile vehicular environments which nodes move fast and topology is very variable. This vehicular network is called Vehicular Ad Hoc Network (VANET) [2] in the literature. In VANETs wireless-equipped vehicles traveling along of a road form a spontaneous network.

Having a promising data dissemination mechanism seems very necessary in VANETs. In context of safety message notification, disseminating a packet beyond the transmission range of its originator is a necessity in most of the VANETs applications. First possible approach coming to mind is flooding mechanism. Flooding has a simple mechanism: whenever a node receives a packet, it re-forwards (re-broadcasts) that packet. Despite the simple mechanism of flooding, it is struggling with three problems: 1) redundant re-forward: neighbours of a sender all receive the same packet from each other; 2) sever contention: all receiving nodes within the same range strive to obtain the shared channel; 3) collision: due to lack of CTS/RTS, happening multiple transmission at the same time is very likely. These three problems altogether is called broadcast storm problem [3].

Thus, in order to mitigate blind broadcasting of flooding a more intelligent mechanism is required. Many protocols have been proposed to lessen this problem [4-13]. Most of the proposed solutions are based on the fact that the nodes placed within the transmission range of sender selects a candidate to perform the task of re-forwarding. This is often done by farthest node. Note that we mean by sender both original sender (crashed vehicle) and also forwarders (intermediate nodes).

In this paper, first of all for a real-world scenario we fully implemented IVG algorithm. This work has been done under CVT-project [13]. This project is initiated by Academic Center for Education, Culture & Research (ACECR)- Sharif branch, Tehran, Iran. One the defined application in this project is accident-notification through multi-hop transmission. In addition to the achieved industrial advantages of this application, it serves as beneficial academic benchmark for other realistic applications in this field. Settings and details of the application have been presented in section 3.

This work is supported by CVT (Connected Vehicle Technology)

project at ACECR-Sharif Branch under Contract with the IDRO (Industrial

Development and Renovation Organization of Iran)

As was mentioned before, one of the interesting algorithms for solving broadcast storm problem is Inter-Vehicle Geocast (IVG) [6]. In IVG every node within the transmission range of sender puts off its sending as much as a specific time which is known as defer time. This time is inversely proportional to the distance from sender.

However, in IVG, when several nodes are approximately at the same distance from a sender, they all obtains the same defer time, and multiple transmission may happen. The reference [11] has coined the term of spatial broadcast storm problem for this problem. Therefore, we propose a beacon based algorithm called Context Aware Geocast Forwarding Protocol (CAGFP). As the name of this protocol suggests, it benefits from topology awareness. Detail and mechanism of this algorithm is presented in section 4.

The rest of this paper is as follows. In section 2 an overview of related works is presented. Section 3 is devoted to description of accident notification application accomplished under CVT project [13]. In section 4 we present the CAGFP proposed algorithm. Section 5 contains simulation results programmed in Veins simulator framework [14]. This paper concludes in section 6.

II. RELATED WORKS

Generally there are several categories of approaches for solving broadcast storm problem. In probability-based approach, whenever a node receives a packet, it re-forwards it with probability p. This method is known as p-persistence approach. Simplest version of this method is 1- persistence. Another type is a gossip-based approach taking advantage of a pre-determined probability. This mechanism is usually referred to probabilistic flooding [12]. Both 1-persistance and probabilistic flooding exceeds in number of re-forwards. Thus, in [4] probability p is computed according to the node’s distance from forwarder in a way that distant nodes re-forward the packet more likely than nearby ones.

In slotted time approach, time is supposed to be fragmented into several time slots. Two techniques for slotted time have been proposed in [4]. In slotted 1-persistance, when a vehicle receives a packet, it assigns a time slot for re-forwarding the packet provided that no one else re-forwards it prior to this time slot. Distant vehicles allocate shorter time slots compared to nearby ones. Besides, the authors of [4] have proposed slotted p-persistence in which similar to 1-persistance version, re-forward is carried out at time slot manner, yet with pre-determined probability p.

In priority-based technique [5], nodes having time-critical messages will be assigned higher priority to access the channel. Indeed, priority-based technique classifies the network into several classes having different priorities. Although this technique is not designed to solve the broadcast storm problem, it can indirectly mitigate the severity of the storm by allowing nodes with higher priority to access the channel as quickly as possible [4].

Authors of [9] have proposed a continuous time approached called Role Based Multicast (RBM) method. According to this scheme, upon receiving a packet by a node, it waits for a specific time and re-forwards the message.

Farther vehicles from a sender wait more and vice versa. RBM is based on maintaining a list of neighbours within the transmission range. Although, this method prevents from gratuitous message broadcast [6], it causes the network to be overwhelmed by periodic information message broadcasts. Besides, it does not consider track detection which itself reduces the accuracy. Two other role based algorithms have been proposed in [10]: TRADE (TRAck Detection) and DDT (Distance Defer Time). TRADE is the same as RBM except that it specifies positions and direction of neighbor vehicles. DDT inserts defer time slots for rebroadcasting of each message. A vehicle executing DDT determines if rebroadcasting of its alarm message can be dropped or not, after defer time is expired. However, DDT is not suitable for light-crowded highways [6]. Simulation results in [10] argue its performance for low density scenarios. IVG [6] algorithm is an algorithm covering part of the problems of RBM, TRADE, DDT. This algorithm is fully distributed in a way that there is no need to extra messages exchanges between nodes aiming at maintaining a list of neighbors at each time.

In our proposed algorithm, since we take advantage of beacon dissemination, each node precisely determines its neighbors through location information captured from received beacon messages. As a result, existing overhead by redundant information messages in other algorithms is vanished here, and also problem of IVG in platoon configuration of nodes is resolved promisingly. At the end of this section, we refer the readers to survey [15] for more results and algorithms about routing in VANETs.

III. TEST-BED IMPLEMENTATION OF THE IVG

Although timely informing the drivers moving on a roadway about an accident is very crucial in inter-vehicular applications, some of the vehicles may not be relevant to this accident. For example in Fig.1, the vehicles behind (a) (crashed vehicle) moving at same direction of (a) and the vehicles in front of (a) moving oppositely of it all are considered to relevant vehicles. Gray areas in Fig. 1 show where relevant vehicles exist in them. Note that the irrelevant vehicles not only do not inform the drive, but do not participate in forwarding process as well.

Figure 1. Relevant areas vehicle (a) has crashed.

In IVG, each vehicle sets a timer for each receiving packet. If the same packet receives from the same transmission range before timer expiration, the timer is cancelled and the vehicle refrains from re-forwarding the packet. This is due to the fact that if another vehicle re-forwards the packet, it is behind that vehicle and there is no need to flood the network with

redundant packets. Otherwise, the packet is re-broadcast. Let defertime(x) denotes value of this timer. In the meantime, defer time idea was introduced in [3] and improved in [6]. The defer time of vehicle (x) receiving a packet from other vehicle(s) is inversely proportional to the distance from them in favour of farthest node to be designate as forwarder [6]. Equation (1) shows the defer time calculated by node (x).

ε

εε

R

RRmeMaxDeferTixdefertime sx )(

)(−

×= (1)

Where R is the transmission range and Dsx is the distance between nodes (s) and (x). Variable ε controls the value of obtained defer time. We have set ε=2 which produce a uniform distribution over interval [0, MaxDeferTime]. You can find an extensive investigation about variable ε in [11].

IVG seems straightforward and unsophisticated algorithm for inter-vehicular communication aiming at safety message notification. Nevertheless, in realistic scenario there are some tricky implementation-related points which require to be addressed.

Whenever a vehicle crashes, it creates a notification packet and broadcasts it. This vehicle pastes its longitude, latitude and course (direction of movement) to the packet using the GPS device connected to the OBU device. There is also a field known as hop which is set to zero by accident-stricken node. This field specifies how many hops a packet have been travelled. The crashed vehicle also includes a time stamp of when the packet has been created. Every packet has an ID which identifies the accident uniquely. Finally, there are three fields for longitude, latitude and course of forwarder which are filled by intermediate (forwarder) vehicles. Crashed vehicle periodically broadcast the accident packet at interval of 0.5 second.

We have developed a relevancy function that fully determines the area wherein a vehicle is moving (Fig. 1). This is done by getting GPS information of each node. According to recommendation of traffic experts in the CVT project, informing the driver beyond 600 meters distance from accident is not necessary. Thus, we cover this concern in the program. Transmission range of an OBU device is 300 meters, and MaxDeferTime is set to 400. A 4-vehcile scenario was tested over 10 km of highway between Tehran and Karaj. The results of the test showed timely informing the derives and suitable performance of implemented algorithm. Fig. 2 shows a deployed vehicle equipped with OBU device (white gadget) connecting to GPS which its antenna is attached on the roof of the vehicle in Fig.2. Fig. 3 shows all four vehicles used for field test. Fig. 4 shows test-bed roadway where is the highway between Tehran and Karaj.

Figure 2. An OBU device deployed in a vehicle.

Figure 3. Schematic of vehicles

Figure 4. Test-bed roadway (Tehran-Karaj highway) [16]

IV. PROPOSED ALGORITHM

Despite the straightforwardness of IVG algorithm, in some situations it suffers from collision problem. Density is influential factors which can affect broadcasting scheme. When density increases, within a transmission range, there are more vehicles trying to be candidate for re-forwarding the packet. When two nodes are approximately at the same distance from the sender, according to (2), both of them may obtain the same defertime. For showing this situation, we have conduct an experiment using Veins simulator. Result of this experiment has been shown in Fig. 5. The crashed vehicle (red one) broadcasts an accident notification packet over the

networks. All yellow vehicles are in the transmission range of accident-stricken vehicle. Since they are almost at the same place, according to IVG algorithm, all of them obtain very close values for defer time. Therefore, almost at the same time 7 vehicle re-forward the packet which evidently leads to packet collision. As a result, green vehicles receive no packet about the accident and they misleadingly contemplate that there is no problem in the way ahead.

The cause of the just mentioned situation in IVG stems from the fact that IVG is a distributed algorithm in a way that each vehicle waits independently as much as a computed defer time, then re-forwards the packet. Indeed, if a node had known that there is another vehicle(s) in its behind, it would not have considered itself as eligible forwarder. There is where being aware about the surrounding topology shows its role.

Figure 5. IVG failure. Red vehicle: crashed, yellow vehicles: forwarders

and green vehicles: not informed vehicles.

A. Topology Sensing

In CAGFP protocol each vehicle senses the topology within its transmission range using beacon broadcasting utility running at the background of the network. Each beacon message contains vehicle’s information (location, speed, course, acceleration and etc) required to locate a vehicle at any time. Each vehicle has a list of its neighbours. When a beacon messages receives, the vehicle updates the list. If it contains the information of new vehicle, it will be added to the list. Otherwise, the location of existing vehicle is updated. This list is checked at each beacon interval reception: 100 ms. If no information receives for an entry in the list, the vehicle computes entry’s location with most recent received information. When the location is located beyond the vehicle transmission range, this entry is removed from the list. If more than two consecutive beacon intervals no message receives for an entry in the list, the vehicle infers that this vehicle has been moved out from its transmission range and consequently removes the entry. Note that each vehicle maintains this list in order to be aware from the vehicles placed in its transmission range and be able to draw its local topology efficiently. One should note that the beacon messages are not regarded as extra overhead since these beacons are built-in part of IEEE 802.11p protocol. Indeed, these beacons periodically are disseminated throughout the network over control channel. However, one may argue that this capability has not been taken advantage for accident-notification application in CVT project (see section 3). Nevertheless, because of some technical reasons beacon capability has been turned off in the OBU devices. Thus, we could not utilize this option.

B. CAGFP Algorithm

The following algorithm is run by each vehicle upon receiving a packet.

(1) when vehicle (x) receives an accident notification p

(2) update the list of neighbours

(3) for each entry calculates its distance from sender

(4) it calculate its distance from sender and adds to list

(5) sort the list ascending in terms of the distance

(6) if the vehicle is a top of the list

(7) then it re-forwards the p immediately

(8) endif

(9) else

(10) extract vehicle (x) order from list: i

(11) set a timer as much as i×0.5 ms

(12) if no packet received during waiting period

(13) then update and re-forward p

(14) endif

(15) else cancel the timer and refrain from re-forwarding

(16) endelse

Upon receiving an alarm packet, the receiving vehicle

updates the list of its neighbors. Then, it sorts the list containing entries of its neighbor plus itself which is ordered by the distance from sender. After sorting, if the vehicle finds itself at top of list (first entry), it concludes that it is farthest vehicle from sender. If so, it re-forwards the packet in no time. Otherwise (there are other vehicle (s) at farther distance), it waits as much as its order in list multiply at a constant time. Then, if no packet receives by its neighbours, it re-forwards the packet itself. This waiting time serves as guard against distortion from maintained list because some vehicle(s) in the list might has departed the transmission range or even (due to network’s problem) has not received the packet at all. As it will shown in the next section, topology awareness leads to higher performance for CAGFP algorithm compared to IVG.

V. SIMULATION

We evaluate IVG and CAGFP using Veins simulator framework [14].Veins is an open source Inter-Vehicular Communication (IVC) simulation framework composed of an event-based network simulator and a road traffic micro-simulation model. Veins is made up of two distinct simulators, OMNeT++ for network simulation and SUMO for road traffic simulation. Movement of vehicles in the road traffic simulator, SUMO, is reflected in movement of nodes in an OMNeT++ simulation. Nodes can then interact with the running road traffic simulation, e.g. to simulate the influence of IVC on road traffic. We take advantage of these two simulators included in Veins.

Simulation settings have been summarized in Table. 1. Transmission range of each vehicle is set 300 m which conforms with OBU device’s specifications in CVT projects as well. The used roadway is a four-line unidirectional highway of length 100 km. We have considered three different densities: low density with average of 53 veh/km, medium density with 66 veh/km and high density with 90 veh/km at

average. One thousand accident notifications are generated by sender, and are transmitted toward the other vehicle.

TABLE I. SIMULATION SETTINGS

300m Transmission range

1250 s Simulation time

200 Vehicle Number

33.3 m/s Max Speed

90 veh/km High Density

66 veh/km Medium Density

53 veh/km Low Density

4ms MaxDeferTime

All disseminate-based schemes try to convey the packets

as far as possible while shortening the delay of delivery. Aiming at this goal, Fig. 6 shows dissemination delay imposed on packet reception over different distances. First of all, clearly, as the distance increases both algorithms go through more delay. However, CAGFP is always superior to IVG algorithm. This is because of proper selection of forwarders in CAGFP algorithm and its collision less behaviour. CAGFP up to distance of 2 km is able to broadcast the packet near to 10 ms.

Fig. 7 shows number of hops that take for a packet to be delivered to a specific distance. Although CAGFP and IVG packets travel almost the same number of hops, at the same hops CAGFP packets arrive sooner than those of IVG.

In 802.11, a node before sending a packet senses the channel. If channel is busy, it avoids from sending and backs off for a certain time. In order to measure the effect of backoff, we have calculated number of re-broadcasts happened during a packet transmission. In addition to the severing the channel contention, more re-broadcast attempts consumes more bandwidth. Fig. 8 exhibits number of re-broadcasts for both IVG and CAGFP algorithms. As Fig. 8 shows, CAGFP performs better compared to IVG regarding to the number of re-broadcasts. This matter is more conspicuous in high density where IVG forwarder candidates transmit their packet almost at the same time.

Reception rate is an interesting metric which can evaluates the impact of occurred collisions. We define the reception rate as percentage of informed vehicles (in relevant areas) to the total number of vehicles. Reception rate shows the reliability of inter-vehicular communication algorithm. Fig. 9 shows the reception rate of IVG and CAGFP for three defined densities. For all densities CAGFP obtains more reception rate compared to IVG. Besides, CAGFP is a resistance against increasing the density because in all densities CAGFP efficiently selects the forwarders which achieves very high and almost constant reception rate. However, as Fig. 9 demonstrates, for high density IVG decrease drastically.

VI. CONCLUSION

For the accident notification application of the CVT project we proposed the Context Aware Geocast Forwarding Protocol (CAGFP) algorithm. CAGFP takes advantage of

disseminated beacons to alleviate the broadcast storm problem. We are motivated to propose CAGFP after test-bed and simulation implementation of the IVG algorithm which is a major algorithm in this filed. The results of simulation exhibited reduction in delay, hop count decreasing and increasing in reception rate for CAGFP compared to the IVG. As a future work we intend to perform a test-bed evaluation of the CAGFP.

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Figure 6. Dissemination delay a)high density b)medium density c) low density

Figure 7. Hop count at certain distance a)high density b)medium density c) low density

Figure 8. Number of rebroadcast a)high density b)medium density c) low density

Figure 9. Reception rate for different density scenarios