Proposed Supercluster-Based UMBBFS Routing Protocol for Emergency Message Dissemination in Edge-RSU for 5G VANET
Abstract
:1. Introduction
- Communication overhead: Due to its limited bandwidth and mobility, the current combination of insufficient communication technologies results in a large communication overhead. Additionally, incorrect base station, RSU deployment, and network structure limit the network’s capacity to scale, increasing communication overhead.
- High packet loss: Some of the pre-existing works included direct routing. However, the lack of vehicle clustering leads to packet loss. Contrarily, clustering is based on parameters such as direction, velocity, and distance of movement. As a result, stability, reliability, energy efficiency, and packet loss are reduced when choosing the CH. However, these criteria alone are insufficient.
- Transmission delay: The choice of a cluster head or a vehicle performing routing independently by just looking at its information leads to inefficient routing that interferes with packet transport. On the other hand, cluster heads are chosen for emergency message transmission depending on the direction angle. However, while sending messages, additional factors (such as distance, node location, and energy) are not taken into account, causing transmission delays. Additionally, the choice of the forwarder is made based on beacon messages and neighbor locations. However, other factors (such as speed, lane condition, and distance) are not taken into account, causing transmission delays.
- Inefficient emergency message dissemination: The next hop selects the best forwarder based on a single moving direction. However, it results in the distribution of emergency messages being ineffective. Estimates of decision areas are often based only on transmission ranges in existing installations. However, since these factors are ineffective at determining decision areas, message transmission becomes difficult. Dissemination of emergency messages in this situation is limited to atypical cars and accidents. However, another emergency message (such as an ambulance alert or a list of local pharmacies) was not considered, resulting in the ineffective distribution of emergency messages. Additionally, it narrows the selection of practical and reasonably priced transportation choices and worsens traffic congestion on the roadways.
- To mitigate communication overhead, we employ a network construction approach that combines 2D and 3D elements. Furthermore, we establish robust vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) communication channels. These enhancements collectively serve to optimize network communication and efficiency.
- To enhance routing efficiency and bolster routing reliability, a clustering approach is implemented. This clustering technique is designed to improve the overall performance of the routing process within the network.
- To minimize transmission delay and reduce the occurrence of high packet loss, we implemented optimal routing strategies and employed a careful selection process to identify the most suitable forwarder nodes. All of these steps improved the network’s data transmission reliability and efficiency.
- To enhance message transmission, we adopted a strategy that involved selecting decision areas and classifying emergency messages, allowing them to be transmitted effectively in multiple directions and thereby increasing their reach and impact.
2. Literature Review
3. Proposed Method
- Two-dimensional (2D) with 3D grid-based network construction.
- Energy-saving-based super-clustering.
- Hybrid protocol-based path selection.
- DRL-based emergency message dissemination.
3.1. 2D with 3D Grid-Based Network Construction
3.2. Energy Saving-Based Super-Clustering
Fog Node Location Model
- Modified density peak clustering (MDPC) algorithm.
3.3. Hybrid Protocol-Based Path Selection
Urban Multi-Hop Broadcast and Best Forwarder Selection (UMBBFS) Protocol
- Multi-hop broadcast.
- 2.
- Neighboring nodes on the intersecting road.
- 3.
- One-hop delay in multi-direction.
- 4.
- Best forwarder selection.
Algorithm 1: Best forwarder selection algorithm |
Input: List of requesting nodes , forwarder list , Output: Forwarder of 1: Find , for each i M 2: Calculate delay , for each 3: Calculate stability , for each 4: if ( has packets to send) then 5: { 6: for every j , compute by providing high weight to 7: forwarder 8: } 9: end if 10: if ( has packets to send) then 11: { 12: for each j , compute by providing a higher weight to 13: forwarder 14: } 15: end if |
- 5.
- Improved firefly optimization (IFO) algorithm.
3.4. DRL-Based Emergency Message Dissemination
3.4.1. Delay Deep Deterministic Policy Gradient Algorithm
3.4.2. Light Gradient Boosting Machine (LGBM) Algorithm
4. Experimental Results
4.1. Simulation Setup
4.2. Comparative Analysis
4.2.1. Number of Vehicles vs. Throughput
4.2.2. Vehicle Density vs. End-to-End Delay
4.2.3. Vehicle Density vs. Coverage
4.2.4. Vehicle Density vs. Packet Delivery Ratio
4.2.5. Number of Vehicles vs. Packet Received
4.2.6. Vehicles Density vs. Transmission Delay
4.3. Research Summary
Confidence Interval
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Hardware specifications | Hard disk | 300 GB |
RAM | 4 GB | |
Software specifications | Simulation tools | OMNET++, SUMO |
Processor | Intel(R) core™ i5-4590S [email protected] GHZ | |
OS | Windows 10 Pro |
Parameters | Values |
---|---|
Version of OMNET++ | OMNET++ 4.6 |
Version of SUMO | SUMO 0.19.0 |
Number of repetitions | 4 |
Number of vehicles | 100 |
Blockchain node | 1 |
Number of ERSU | 4 |
Controller | 3 |
TAS | 4 |
Log collector | 1 |
Vehicle acceleration | 3.5 m/s2 |
Packet interval | 2 s |
Generated packet number | 100 |
Packet size | 512 |
Number of packets | ~5000 |
Data rate | Max 2 kbps |
Simulation time | 500 s |
Transmission power | 10 mW |
Rate of transmission | 18 Mbps |
Bandwidth | 10 MHz |
Simulation area | 2750 m × 2250 m |
Software between networks | TraCIDemoRSU11p in omnetpp.ini |
Comparison Metrics | Proposed | Fuzzy Broadcast | Multi-Lane mmWave | RSBP-RF |
---|---|---|---|---|
Throughput (kbps) | 3.9 | 3.3 | - | 3.4 |
End-to-end delay | 70 | - | 90 | 87 |
Coverage (%) | 90 | -- | 59 | 70 |
Packet delivery ratio (%) | 98 | 78 | -- | 81 |
Packet received | 12.75 k | 8 k | -- | 1 k |
Transmission delay (ms) | 57 | 86 | -- | 80 |
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Share and Cite
Albeyar, M.A.; Smaoui, I.; Mnif, H.; Alani, S. Proposed Supercluster-Based UMBBFS Routing Protocol for Emergency Message Dissemination in Edge-RSU for 5G VANET. Computers 2024, 13, 208. https://doi.org/10.3390/computers13080208
Albeyar MA, Smaoui I, Mnif H, Alani S. Proposed Supercluster-Based UMBBFS Routing Protocol for Emergency Message Dissemination in Edge-RSU for 5G VANET. Computers. 2024; 13(8):208. https://doi.org/10.3390/computers13080208
Chicago/Turabian StyleAlbeyar, Maath A., Ikram Smaoui, Hassene Mnif, and Sameer Alani. 2024. "Proposed Supercluster-Based UMBBFS Routing Protocol for Emergency Message Dissemination in Edge-RSU for 5G VANET" Computers 13, no. 8: 208. https://doi.org/10.3390/computers13080208