Chapter 2 Background
2.2 Proactive protocols and reactive protocols
Routing protocols can be divided into two basic types: proactive protocols and reactive protocols. Proactive protocols (table-driven), such as FSR [5], DSDV [6], OLSR [7], need to maintain routing tables, by sending periodic control packets, such as RREQ and RREP packets. The main disadvantage of this type of protocols is that it needs to maintain routing tables by periodically sending RREQ packets and RREP packets. That is is has high control overhead. In reactive routing protocols, such as AODV [2] and DSR [3], when there are data packets need to be sent, this type of protocols sends RREQ and RREP packets to construct routes. The main disadvantage is the end-to-end delay needed to construct new routes.
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Chapter 3
Related Work
Our routing protocol is a road-based routing protocol. In sections 3.1 and 3.2, two road-based routing protocols are reviewed. In section 3.3, a routing protocol using parked vehicles is reviewed. Its idea of using stationary vehicles for packet forwarding can support our approach of using vehicles stopping at the red traffic lights for data forwarding. In section 3.4, different routing protocols are compared.
3.1 Connectionless approach (CLA) [10]
The connectionless approach (CLA) is a road-based routing protocol [10]. It can adapt to the change of the network topology rapidly. This protocol does not need to build a routing table to maintain the positions of neighbor nodes, and it does not need to maintain a hop-by-hop route between the source and destination nodes. The nodes belong to the selected cells in the virtual cell list can receive or forward data. When a relay node leaves the selected cell, it is no need to relay data.
However, as shown in Figure 1, cell A and cell C are located in road intersections where nodes would have short time to relay data packets. A relay node in such a cell would not relay data long enough, so a different node needs to be found frequently to relay data. Another disadvantage of this approach is that, in a selected cell, a high speed node may be chosen, which also have short time to relay data packets in the cell if we do not set high backoff delays to nodes with high speeds.
Figure 1. Virtual cell of CLA.
3.2 Road-based routing using real-time vehicular traffic (RBVT) [12]
A number of road-based routing protocols have been proposed recently [18], [19], [20].
However, some early proposed routing protocols utilize the shortest path to create routes that are composed of road segments between the source and the destination nodes. It is possible that there are no nodes on the road segments of the shortest path or route packets toward dead ends. Some other routing protocols try to use historical data such as average traffic flow.
However, historical data may not be accurate in indicating the current road traffic conditions because of accidents or road constructions.
The RBVT protocol utilizes real-time vehicular traffic information obtained from route discovery to create paths consisting of road intersections which may have network connectivity among them with higher probability [12]. The authors proposed RBVT-P
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3.3 Parked Vehicle Assistance (PVA) [17]
PVA allows parked vehicles, which are static nodes, to join VANETs. Parked vehicles can serve as a static backbone and a service infrastructure to improve connectivity. A small proportion (30%) of PVA vehicles could promote network connectivity greatly. According to PVA [17], using stationary nodes to forward data packets can improve the connection ratio (packet delivery ratio) to 80 %, connection duration to 300 seconds and re-healing time to 1 second over 100 nodes. Note that connection duration indicates how frequently the path between two vehicles becomes unavailable. Re-healing time indicates how long the vehicles, once disconnected, need to wait before a new connection established [17].
3.4 Comparison of different routing protocols
As shown in Table 2, we compare the proposed TLR and two existing CLA and RBVT routing protocols. In TLR, vehicles with zero or low mobility would be chosen to forward data. Note that CLA and RBVT do not utilize traffic light information. The proposed TLR performs better than CLA and RBVT-P in terms of packet delivery ratio, and performs better than RBVT-R in terms of end-to-end delay.
Table 2. Comparison of different road-based routing protocols
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Chapter 4
Proposed Traffic Light Based Routing
The proposed Traffic Light based Routing (TLR) is a road-based routing protocol. The equipment required for this protocol is a global positioning system (GPS) and a digital map which are built in a car. When vehicles stop at red traffic lights, the vehicles with no mobility would be chosen to forward data packets to next nodes. A road area is divided into a number of virtual cells and a traffic light cell is included in a virtual cell. Route discovery to select a list of virtual cells to be a packet forwarding path between source and destination nodes.
4.1 Virtual cell IDs
Figure 2 shows an example of specifying virtual cell IDs, where virtual cell IDs are specified on road intersections. Road intersections in urban areas usually have traffic lights.
Red lights on means nodes must stop at road intersections. Using reliable and stable nodes at road intersections to relay data packets may increase the packet delivery ratio and reduce the end-to-end delay.
S
Figure 2. An example of specifying virtual cell IDs on road intersections.
A source node sends data packets according to its virtual cell record. A virtual cell record includes the selected virtual cell IDs which represent a route. The header of a data packet includes source address, destination address, virtual cell record, current virtual cell ID, and sequence number. The virtual cell ID represents a road intersection area, which has traffic lights. The nodes send data packets to relay nodes which are waiting for red traffic lights to
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We set nodes’ priorities by backoff delay computation when nodes receive data packets. The backoff delay computation is depicted in section 4.5. If there is no node located in a traffic light cell, the nodes located in the rest of the virtual cell will be chosen to relay data packets.
Virtual priority to relay data in a traffic
light cell
If there is no node in a traffic light cell, choose a relay node in the corresponding
virtual cell
Traffic light
Figure 3. A road map is divided into virtual cells and a traffic light cell is included in a virtual cell.
4.3 Route discovery
The mechanism of our route discovery is based on CLA [10]. If a source node does not have any route information to the destination node, it broadcasts RREQ packets to find out the destination node. The header of an RREQ packet includes a sequence number which uniquely identifies the packet, source node ID, source node’s virtual cell ID, destination node ID, destination node’s virtual cell ID and virtual cell record which records a list of virtual cells. If an intermediate node receives the same sequence number of an RREQ packet, it discards the packet to avoid broadcasting duplicated packets. If not, the intermediate node attaches its current virtual cell ID into the virtual cell record and forwards the RREQ packet. When the destination node receives the RREQ packet, and it then records its current virtual cell ID and
its direction into an RREP packet. Finally, it sends the RREP packet back to the source node along the route specified in the virtually cell record.
4.4 Data forwarding
The flowchart of data forwarding from source to destination nodes is shown in Figure 4. A data packet is transmitted from the source to the destination nodes according to a list of selected virtual cell IDs. When a node receives a data packet, it checks if itself is the destination. If it is the destination, stop transmitting; otherwise, it checks if its node’s virtual cell ID is in the virtual cell ID record. If the node’s virtual cell ID is not in the virtual cell ID record, it discards the data packet; otherwise, it runs backoff delay computation. Relay nodes run backoff delay computation to avoid collisions. If a node’s backoff delay is shorter, it has higher priority to relay data packets. The details of the backoff delay computation is described in the next section.
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Figure 4. Flowchart of a node forwarding a data packet from source to destination nodes.
4.5 Backoff delay computation
The backoff delay computation of noden receiving a data packet in a traffic light cell of a virtual cell is computed as follow:
where α is a random number in microseconds (0 ≦ α < 51.2), ɣ is a delay threshold, and Spdn is the speed of noden.
The backoff delay computation of noden receiving data packet in the rest of the virtual cell is computed as follow:
where β is a random number in microseconds (51.2 ≦ β < 102.4), λ is a delay threshold, Distnm is the current distance between node n and the previous node m, and MAX_DIST is the maximal radio range.
The backoff delay computation of nodei receiving data packet in a traffic light cell of a virtual cell and in the rest of the virtual cell is summarised as follow:
Backoff delay computation is run on every node for data forwarding. According to the
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4.6 An example of data forwarding
Figure 5 shows an example of data forwarding. There are some nodes waiting in a traffic light cell when traffic lights turn red. Since nodes are waiting for the red traffic lights to turn green, those nodes with no mobility, such as the node with 0 km/hr, will be chosen to forward data. If no node in traffic light cell, a node which is the farthest from the previous sender are located in the rest of the virtual cell will be chosen to forward data.
Figure 5. An example of data forwarding.
Chapter 5
Simulation and Discussion
For simulation, we chose GlomoSim [16] to evaluate the proposal routing protocol, TLR.
GlomoSim is an open source network simulator developed at UCLA and its layered approach is similar to the OSI five-layer network architecture [10].
5.1 Simulation setup
We used two urban scenarios in order to compare the performance of the proposed TLR with two road-based routing protocols, CLA [10] and RBVT [12]. For Glomosim, the area is either 1000 m * 1000 m or 1500 m * 1500 m. The detailed settings of Glomosim are given in Table 3. We chose the VanetMobiSim [14] mobility model to generate mobility traces for simulation. The simulation terrain size is either 1000 m * 1000 m or 1500 m * 1500 m and nodes are placed randomly in the area. A minimum speed of a node is 1 m/s and 11.1 m/s and the maximum speed of a node is 15 m/s and 24.4 m/s for two simulation settings. The number of nodes range from 50 to 250 nodes, the time interval between traffic lights change is set to be 40 seconds, and the radio range of a node is 376 m. The detailed settings of VanetMobiSim
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• End-to-end delay: this number indicates the average time from the beginning of a packet transmission (including route acquisition delay) at a source node until packet delivery to a destination measured in millisecond [13].
• Control overhead: it measures the number of routing packets transmitted per distinct data packet delivered to a destination [15].
Table 3. Simulation settings for GlomoSim [16].
Parameters Setting 1 Setting 2
Simulation time(s) 900 300 [12]
Mobility model VanetMobiSim VanetMobiSim
Terrain dimensions 1000 m * 1000 m 1500 m * 1500 m [12]
MAC protocol 802.11 802.11
Source-destination pairs 5 5
Data traffic generation CBR CBR
Packet size (byte) 512 512
Radio transmission range 376 m 376 m
Table 4. Simulation settings for VanetMobiSim [14].
Parameters Setting 1 Setting 2
Simulation time(s) 900 300 [12]
5.2 Simulation results and discussion
In Figure 6, we compare the packet delivery ratio for number of nodes from 50 to 200 between the proposed TLR and CLA routing protocols. The detailed settings for Glomosim and VanetMobiSim are shown in setting 1 of Table 3 and setting 1 of Table 4, respectively.
Simulation results show that a larger number of nodes results in a larger packet delivery ratio, due to the increase of network connectivity. The proposed TLR improves the packet delivery ratio by 10.5% compared to CLA, because TLR utilizes stationary nodes or low velocity nodes located in traffic light cells to forward data packets. That is, the routing paths between stationary nodes or low velocity nodes are more reliable [17]. In Figure 7, we compare the end-to-end delay for number of nodes from 50 to 200 between TLR and CLA. Simulation result shows that the proposed TLR improves the end-to-end delay by 29.4 ms compared to CLA. This is because TLR uses the backoff delay computation to avoid collisions and retransmissions. In Figure 8, we compare the control overhead for number of nodes from 50 to 200 between TLR and CLA. Simulation result shows that the proposed TLR improves the control overhead by 0.52 packets compared to CLA. This is due to that TLR uses the backoff delay computation to avoid collisions and retransmissions.
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Figure 6. Effect of different number of nodes on packet delivery ratio.
Figure 7. Effect of different number of nodes on end-to-end delay.
Figure 8. Effect of different number of nodes on control overhead.
In Figure 9, we compare the packet delivery ratio under packet rates from 0.5 to 5 packets/s between TLR, CLA and RBVT-P routing protocols. The detailed settings for
Glomosim and VanetMobiSim are shown in setting 2 of Table 3 and setting 2 of Table 4, respectively. Simulation result shows that the proposed TLR performs well, with an improvement of 10.7% packet delivery ratio compared with CLA. TLR has an improvement of 10% packet delivery ratio compared with RBVT-P. In Figure 10, we compare the end-to-end delay under packet rates from 0.5 to 5 packets/s between TLR, CLA and RBVT-P.
Simulation result shows that the proposed TLR has better end-to-end delay than CLA and
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Figure 9. Effect of different packet rate on packet delivery ratio.
Figure 10. Effect of different packet rate on end-to-end delay.
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Chapter 6 Conclusion
6.1 Concluding remarks
We have presented a traffic light based routing (TLR) protocol for VANETs that is based on traffic lights of urban areas. An area is divided into numbers of virtual cells and a traffic light cell is included in a virtual cell. When vehicles stop at red traffic lights, nodes with no mobility are selected to forward data to next nodes reliably. Using stable nodes selected by running backoff delay computation to relay data packets can increase the packet delivery ratio and reduce the end-to-end delay. Simulation has shown that the proposed TLR improves 10.5% and 10% of the packet delivery ratio compared to CLA and RBVT-P, respectively. The proposed TLR also reduces 21.3 ms and 82.5 ms of the end-to-end delay compared to CLA and RBVT-P, respectively. Although RBVT-R has the better packet deliver ratio than TLR, its end-to-end delay is much higher than TLR. Delivering packets to a relay vehicle which is waiting for a red traffic light and running backoff delay computation indeed can improve the packet delivery ratio and the end-to-end delay.
6.2 Future work
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