Weight-Based PA-GPSR Protocol Improvement Method in VANET
Abstract
:1. Introduction
- (1)
- We improve the location-based routing protocol in VANET.
- (2)
- Two node selection strategies based on weight are proposed, and the next hop node is selected according to the following parameters: reliable node density, node location, node movement direction, node cumulative communication duration, and data packet delivery angle.
- (3)
- We study the impact of the number of different nodes on performance through the proposed strategy.
2. Related Work
3. Formation of Weighted Path Aware Greedy Perimeter Stateless Routing Protocol
3.1. Influence of Node Movement Direction on Communication Reliability
3.2. Influence of Reliable Node Density on Communication Reliability
3.3. Influence of Cumulative Communication Duration on Communication Reliability
4. Proposed Protocol
4.1. System Model and Assumptions
- (1)
- Location and radius: each vehicle was equipped with a Global Positioning System (GPS) and OBU, which have fixed accessible communication ranged [36]. OBU enabled the vehicle to send a beacon within its communication range to perform inter-vehicle communication. In W-GPSR, similar to most geographic routing protocols, it was assumed that there is a centralized location service. Each forwarding node could obtain destination location information by querying the central management organization to meet routing requirements.
- (2)
- Communication and sensors: each vehicle was equipped with a wireless network interface that complies with 802.11p or dedicated short-range communication standards for inter-vehicle communication [34]. In addition, each vehicle was also equipped with an onboard diagnostic interface, which was designed to obtain data from multiple mechanical and electronic sensors in the vehicle. There was no infrastructure around the road, and nodes can only exchange data through V2V.
- (3)
- Neighbors and paths: the initial location of the vehicle was determined based on a random selection of uniform distribution. When vehicles were within communication range of each other, an edge connection was established between their neighbors. Communication could be established based on direct contact with each other or through neighbors. Due to the dynamic nature of VANET, communication had to be established iteratively using dynamic routing protocols.
- (4)
- Nodes share information: these data included information about modes’ state vectors, such as physical location, destination, and direction.
- (5)
- Model area: the model area was constrained by the plane frame. The network model consisted of roads and intersections that simulated a typical urban environment. The system scenario diagram is shown in Figure 4.
- (6)
- The location information provided by the positioning system was accurate, i.e., the location error was not considered.
4.2. System Architecture and Data Structure
4.3. Vehicle Follow-Up Model
4.4. Packet Queuing Model
4.5. Greedy Forwarding Route Establishment Strategy Based on Weight
4.6. Perimeter Forwarding Route Maintenance Strategy Based on Weight
4.7. The Overall Process of the Protocol
Algorithm 1: W-PAGPSR. |
Input: Source node ; Destination node ; Output: Best relay node; 1. While is the receive packet, is 2. If , then 3. The best relay node is ; 4. If is HELLO packet, then 5. Use the content in to update or create the content in , such as the number of neighbors, location, co-ordinates, speed, etc. 6. End if 7. If is the data packet, then 8. If using greedy forwarding mode, then 9. Calculate and according to formula (5) 10. For (All neighbors in and ) do 11. Calculate angle according to Formula (6) 12. Calculate according to Formula (1) 13. Calculate according to Formula (8) 14. Calculate according to Formula (4) 15. If then 16. 17. 18. End if 19. End for 20. Update and then forward to 21. Else 22. For (All neighbors in ), perform the following actions 23. Calculate and according to Formulas (10) and (11) 24. Calculate according to Formula (8) 25. Calculate and according to Formula (9) 26. If is in the left half plane and , then 27. 28. 29. End if 30. If is in the right half plane and , then 31. 32. 33. End if 34. End for 35. If , then 36. 37. Else 38. 39. End if 40. Update and forward to 41. End if 42. End if 43. End while |
4.8. Algorithm Complexity
5. Simulation and Performance Analysis
5.1. Simulation Parameter Setting
5.2. Result Analysis
- (1)
- Packet loss rate: the ratio of the total number of lost data packets to the total number of data packets PL.
- (2)
- Throughput: the amount of information successfully transmitted per unit time via the communication channel. The greater the throughput, the shorter the time the algorithm requires to send the same number of data packets.
- (3)
- Average end-to-end delay: the average of the delay Dn of all successfully received packets. The MAC protocol affects the transmission delay, and the use of the standard 802.11PMAC protocol is considered in the [41].
5.2.1. Packet Loss Rate
5.2.2. Throughput
5.2.3. Average End-to-End Delay
6. Conclusions
- (1)
- Firstly, in the routing establishment stage, the distance, reliable node density, cumulative communication duration, and node movement direction are used to establish a greedy forwarding weight strategy; secondly, in the routing maintenance stage, the packet delivery angle and reliable node density are used to establish a perimeter forwarding weight strategy, and the weight parameters are then calculated using the CRITIC method; and, finally, a highly reliable link is established as a communication route.
- (2)
- Based on the NS-3 and SUMO simulation platforms, the two strategies are simulated and compared to other geographic location routing protocols in urban scenarios with different traffic densities and CBR connections. Compared to GPSR, MM-GPSR, and PA-GPSR in 30–110 nodes and 5–20 CBR connections, the packet loss rate of the protocol is reduced by an average of 24.47%, 25.02%, respectively; and 14.12%, the average end-to-end delay is reduced by an average of 48.34%, 79.96%, and 21.45%, respectively; and the network throughput is increased by an average of 47.68%, 58.39%, and 20.33% respectively.
- (3)
- According to the time complexity analysis, compared to GPSR, MM-GPSR, and PA-GPSR, W-PAGPSR does not add to the time complexity.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Protocol | Scenario | Selection Parameters | Communication | Forwarding Mechanism | Recovery Mechanism | Performances Metrics | Sender/ Receiver Oriented |
---|---|---|---|---|---|---|---|
GPSR [14] | Highway | Distance | V2V | Greedy forwarding | Perimeter forwarding | Packet loss rate and overhead | Sender-oriented |
GPSRJ+ [15] | Highway | Distance, direction, and speed | V2V | Improved greedy forwarding | Improved perimeter forwarding | Packet delivery rate, delay, throughput, and overhead | Sender-oriented |
MM-GPSR [16] | Urban | Cumulative communication duration | V2V | Improved greedy forwarding | Improved perimeter forwarding | Packet loss rate, delay, and throughput | Sender-oriented |
PA-GPSR [17] | Urban | Distance | V2V | Improved greedy forwarding | Improved perimeter forwarding | Packet loss rate, delay, and network yield | Sender-oriented |
PGRP [18] | Urban and highway | Distance, direction, and angle | V2V | Predictive greedy forwarding | Predictive perimeter forwarding | Packet delivery rate, delay, and hop count | Sender-oriented |
K-PGRP [19] | Urban and highway | Distance, direction, and angle | V2V | Predictive greedy forwarding | Predictive perimeter forwarding | Packet delivery rate and throughput | Sender-oriented |
MPBRP [20] | Urban | Distance, direction, and angle | V2V | Predictive greedy forwarding | Predictive perimeter forwarding | Packet delivery rate, delay, and hop count | Sender-oriented |
W-GPCR [21] | Urban | Distance, direction, and density | V2V | Improved greedy forwarding | Improved perimeter forwarding | Packet delivery rate, delay, and hop count | Sender-oriented |
HRNS [22] | Highway | Distance, traffic load, speed, and density | V2V | Hybrid relay node selection scheme | _ | Reachability, delay, and saved rebroadcast | Sender-oriented |
Geo-LU [23] | Urban | Residual bandwidth and link quality | V2V | Two-hop information-based greedy forwarding | _ | Packet delivery rate, throughput, and overhead | Sender-oriented |
TGRV [24] | Urban | Distance, speed, direct trust, recommendation trust, and direction | V2V | Trust-based greedy forwarding | Trust-based perimeter forwarding | Packet delivery rate, delay, and hop count | Sender-oriented |
SFTD [25] | Urban | Link quality | V2V | Smart data dissemination strategy | _ | Packet delivery rate, delay, and throughput | Receiver -oriented |
ReUse [26] | Highway | Mobility, link quality, buffer size, and the number of neighbors | V2V, V2I, and I2I | Relay selection using harmony search and fuzzy analytic hierarchy process | _ | Packet delivery rate, packet sent rate, delay, reachability, collision rate, redundancy rate, and throughput | Receiver -oriented |
OPBRP [27] | Urban | Distance, direction, position, and speed | V2V and V2I | Predictive greedy forwarding | Predictive perimeter forwarding | Packet delivery rate, delay, power consumption, and hop count | Sender-oriented |
Geo-CAP [28] | Urban | Bandwidth availability and link quality | V2V | Improved greedy forwarding | Carry-and-forward strategy | Packet delivery rate, delay, and throughput | Sender-oriented |
MCBS [29] | Urban and highway | Distance, density, angle, link stability, and velocity | V2V | Contention-based forwarding | _ | Packet delivery rate, delay, hop count, and throughput | Receiver-oriented |
REMR [30] | Highway | Position, distance, speed, and moving angle | V2V | Improved greedy forwarding | Carry-and-forward strategy | Packet delivery rate, delay, and hop count | Sender-oriented |
MISP [31] | Urban | Distance, density, road connectivity, and link stability | V2V | Multiple intersection selection routing algorithm | _ | Packet delivery rate and delay | Sender-oriented |
TLBGR [32] | Urban | Density, road connectivity, and link stability | V2V and V2I | Next link segment selection and next hop selection based on trunk line | _ | Packet delivery rate, delay, and overhead | Sender-oriented |
ISR [33] | Urban | Distance, density, direction, and link stability | V2V | Information dissemination-centric routing | _ | Packet delivery rate, delay, and throughput | Sender-oriented |
Name | Size |
---|---|
The package type | 2 bytes |
The x co-ordinate of the sender | 8 bytes |
The y co-ordinate of the sender | 8 bytes |
The number of neighbors | 4 bytes |
Name | Size |
---|---|
The package type | 2 bytes |
The x co-ordinate of the destination | 8 bytes |
The y co-ordinate of the destination | 8 bytes |
The exact time when the location was last updated | 4 bytes |
The x co-ordinate of entering the perimeter mode | 8 bytes |
The y co-ordinate of entering the perimeter mode | 8 bytes |
The perimeter mode flag | 1 byte |
The x co-ordinate of the previous hop | 8 bytes |
The y co-ordinate of the previous hop | 8 bytes |
Greedy Forwarding | Perimeter Forwarding | |
---|---|---|
GPSR | ||
MMGPSR | ||
PA-GPSR | ||
W-PAGPSR |
Parameter | Value |
---|---|
Data packet size/B | 512 |
Simulation time/s | 200 |
Simulation area/m2 | 1100 × 1100 |
Number of nodes | 30, 50, 70, 90, 110 |
HELLO interval/s | 1 |
Number of CBR connections | 5, 10, 15, 20 |
Transport protocol | UDP |
Maximum speed/(m·s−1) | 15 |
Channel data rate/(Mbit·s−1) | 3 |
MAC protocol | IEEE 802.11p |
Packet interval/s | 0.2 |
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Zhang, W.; Jiang, L.; Song, X.; Shao, Z. Weight-Based PA-GPSR Protocol Improvement Method in VANET. Sensors 2023, 23, 5991. https://doi.org/10.3390/s23135991
Zhang W, Jiang L, Song X, Shao Z. Weight-Based PA-GPSR Protocol Improvement Method in VANET. Sensors. 2023; 23(13):5991. https://doi.org/10.3390/s23135991
Chicago/Turabian StyleZhang, Wenzhu, Leilei Jiang, Xi Song, and Zhengyuan Shao. 2023. "Weight-Based PA-GPSR Protocol Improvement Method in VANET" Sensors 23, no. 13: 5991. https://doi.org/10.3390/s23135991
APA StyleZhang, W., Jiang, L., Song, X., & Shao, Z. (2023). Weight-Based PA-GPSR Protocol Improvement Method in VANET. Sensors, 23(13), 5991. https://doi.org/10.3390/s23135991