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Vehicular Ad-Hoc Networks for Intelligent Transportation System: A Brief Review of Protocols, Challenges, and Future Research Bintoro, Ketut Bayu Yogha
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2125

Vehicular Ad Hoc Networks (VANET) play an essential role in the advancement of intelligent transportation systems, facilitating real-time communication between vehicles (V2V), infrastructure (V2I), and surrounding environments (V2X). This systematic review analyzes a range of VANET routing protocols, highlighting the strengths and weaknesses of topology-based, position-based, cluster-based, and hybrid methods. Additionally, this review explores core challenges in VANET, including high mobility, data security, Quality of Service (QoS) requirements, and connectivity issues in dynamic and high-density traffic environments. The paper also provides insights into simulation tools and performance metrics employed in VANET research alongside practical applications in modern transportation systems, such as autonomous driving, traffic management, and safety-related communication. Furthermore, this review emphasizes the need for ongoing research to address the identified challenges and optimize VANET performance. Integrating emerging technologies, including 5G, artificial intelligence (AI), and edge computing, offers promising avenues for enhancing system efficiency and sustainability. This review establishes a comprehensive foundation for further advancements in VANET by highlighting key findings and research gaps. Ultimately, the effective implementation of VANET has the potential to significantly improve transportation safety, efficiency, and sustainability, contributing to the realization of smart city initiatives and innovative mobility solutions. This work aims to guide future research directions, ensuring that VANET continues to evolve in alignment with the demands of modern transportation systems and the broader context of intelligent mobility.

Smart AODV Routing Protocol Strategies Based on Learning Automata to Improve V2V Communication Quality of Services in VANET Bintoro, Ketut Bayu Yogha; Priyambodo, Tri Kuntoro; Sardjono, Yadie Prasetyo
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 3, August 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i3.1969

The Adhoc On-Demand Distance Vector (AODV) protocol faces challenges in selecting the best relay nodes, which requires optimization to improve performance in Vehicular ad-hoc networks (VANETs). This study aims to enhance Vehicle-to-Vehicle (V2V) communication in VANETs by implementing the Learning Automata-Driven Ad-hoc On-Demand Distance Vector (LA-AODV) routing protocol. LA-AODV is designed to achieve higher packet delivery ratios and optimize data transfer rates, even under congested network conditions, by dynamically adjusting to changing network scenarios. The performance evaluation includes six key metrics analyzed under varying node densities and time intervals, comparing LA-AODV against the standard AODV protocol. Results indicate that LA-AODV consistently outperforms AODV, demonstrating improved efficiency in flood identifier management, reduced data loss, higher packet delivery ratios, better throughput, and reduced end-to-end delay and jitter. Specifically, under a 20-node scenario, LA-AODV exhibits lower flood ID scores (54 vs. 88), reduced packet loss (11% vs. 12%), higher PDR (88.0% vs. 87.0%), and superior throughput (85.34 Kbps vs. 47.26 Kbps). Additionally, LA-AODV achieves lower end-to-end delay (6.84E+09 ns vs. 3.76E+10 ns) and jitter (2.52E+09 ns vs. 2.15E+10 ns). These findings suggest that LA-AODV significantly enhances Quality of Service (QoS) in vehicular ad-hoc networks, positioning it as a promising solution for optimizing V2V communication performance.

Quality of Service Comparison of DSDV and DSR Routing Protocols for V2V Communication in VANET bintoro, ketut bayu yogha; Mukholladun, Muhammad Wildan
JITCE (Journal of Information Technology and Computer Engineering) Vol 8 No 2 (2024): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.73-82.2024

The study evaluates the Quality of Service (QoS) performance of the Destination-Sequenced Distance Vector (DSDV) and Dynamic Source Routing (DSR) protocols in vehicle-to-vehicle (V2V) communication within a Vehicular Ad-Hoc Network (VANET) environment. Simulations were conducted to analyze key QoS metrics, including throughput, delay, and routing overhead, under various traffic densities and network dynamics. The results reveal that DSR excels in scenarios with rapid topology changes due to its lower routing overhead. At the same time, DSDV provides better route stability in less dynamic conditions, ensuring consistent performance. These findings underscore the importance of matching routing protocols to the specific requirements of V2V applications, such as real-time data exchange or traffic safety, to ensure informed decision-making. The study also highlights the potential for a hybrid protocol that integrates the stability of DSDV with the efficiency of DSR to address diverse VANET challenges and enhance overall QoS performance

Vehicular Ad-Hoc Networks for Intelligent Transportation System: A Brief Review of Protocols, Challenges, and Future Research Bintoro, Ketut Bayu Yogha
JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i2.2112

Vehicular Ad Hoc Networks (VANET) play an essential role in the advancement of intelligent transportation systems, facilitating real-time communication between vehicles (V2V), infrastructure (V2I), and surrounding environments (V2X). This systematic review analyzes a range of VANET routing protocols, highlighting the strengths and weaknesses of topology-based, position-based, cluster-based, and hybrid methods. Additionally, this review explores core challenges in VANET, including high mobility, data security, Quality of Service (QoS) requirements, and connectivity issues in dynamic and high-density traffic environments. The paper also provides insights into simulation tools and performance metrics employed in VANET research alongside practical applications in modern transportation systems, such as autonomous driving, traffic management, and safety-related communication. Furthermore, this review emphasizes the need for ongoing research to address the identified challenges and optimize VANET performance. Integrating emerging technologies, including 5G, artificial intelligence (AI), and edge computing, offers promising avenues for enhancing system efficiency and sustainability. This review establishes a comprehensive foundation for further advancements in VANET by highlighting key findings and research gaps. Ultimately, the effective implementation of VANET has the potential to significantly improve transportation safety, efficiency, and sustainability, contributing to the realization of smart city initiatives and innovative mobility solutions. This work aims to guide future research directions, ensuring that VANET continues to evolve in alignment with the demands of modern transportation systems and the broader context of intelligent mobility.

Quality of Service Comparison of DSDV and DSR Routing Protocols for V2V Communication in VANET bintoro, ketut bayu yogha; Mukholladun, Muhammad Wildan
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.73-82.2024

The study evaluates the Quality of Service (QoS) performance of the Destination-Sequenced Distance Vector (DSDV) and Dynamic Source Routing (DSR) protocols in vehicle-to-vehicle (V2V) communication within a Vehicular Ad-Hoc Network (VANET) environment. Simulations were conducted to analyze key QoS metrics, including throughput, delay, and routing overhead, under various traffic densities and network dynamics. The results reveal that DSR excels in scenarios with rapid topology changes due to its lower routing overhead. At the same time, DSDV provides better route stability in less dynamic conditions, ensuring consistent performance. These findings underscore the importance of matching routing protocols to the specific requirements of V2V applications, such as real-time data exchange or traffic safety, to ensure informed decision-making. The study also highlights the potential for a hybrid protocol that integrates the stability of DSDV with the efficiency of DSR to address diverse VANET challenges and enhance overall QoS performance

Revolusi Sistem Transportasi Cerdas: AODV Berbasis Learning Automata untuk Peningkatan Komunikasi V2V di Jalan Bebas Hambatan Bryan Jonathan Hutapea; Ketut Bayu Yogha Bintoro; Helna Wardhana
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.5131

Backgroud: Vehicle-to-vehicle communication has become a crucial element in the development of intelligent transportation systems. However, conventional routing protocols face limitations in coping with dense and dynamic traffic conditions. Objective: The objective of this study is to improve communication efficiency between vehicles by modifying an on-demand routing protocol using a learning automata approach. Method: This study employed a simulation method with traffic modeling using traffic modeling software and network simulation tools, based on data from highways in the Soekarno-Hatta International Airport area. Result: The results of this study show that the developed protocol increases the packet delivery ratio to 87.7% and reduces latency by 6.5%. Conclusion: The conclusion of this study is that the application of learning automata in vehicle routing enhances communication reliability and supports the implementation of a more adaptive and efficient transportation system.

Learning Automata Based-AODV Routing Protocol for Inter-vehicle Communication: A Simulation Approach Ikhwan , Muhammad Khoirul; Yogha Bintoro, Ketut Bayu
Jurnal PROCESSOR Vol 20 No 1 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.1.2209

The Ad-hoc On-Demand Distance Vector (AODV) routing protocol is a Mobile Ad-hoc Network (MANET) routing protocol that is experimentally used in Vehicular Ad-hoc Networks (VANETs) to support Vehicle-to-Vehicle (V2V) communication. Unfortunately, the standard AODV can lead to degraded responsiveness due to excessive information flow in the VANET environment. The research proposed a Learning Automata-based AODV (LA-AODV) that integrates reinforcement learning for enhanced relay node selection and communication responsiveness in VANET. By considering real-time vehicle parameters during relay node selection, LA-AODV optimizes Quality of Service (QoS) and indirectly reduces road incidents. Simulation results using Network Simulator 3 (NS-3) in a grid traffic scenario demonstrate and validate that LA-AODV outperforms AODV regarding Packet Delivery Ratio (PDR), average end-to-end delay, throughput, and communication overhead. Using Learning Automata for relay node selection in LA-AODV improves the QoS of V2V communication, making it suitable for applications in smart transportation and intelligent vehicle networks supported with V2V communication in each vehicle. This research contributes to the field by improving the AODV protocol for V2V communication, especially in VANET research

Optimasi Protokol Komunikasi V2V untuk Lalu Lintas Perkotaan dan Jalan Raya dengan AODV Berbasis Learning Automata Sadiah, Hanna Halimatu; Bintoro, Ketut Bayu Yogha; Letsoin, Fita Sari; Bintoro, Ketut Bayu
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 1 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i1.15837

This research addresses optimizing communication efficiency in Vehicle-to-Vehicle (V2V) networks in urban and highway environments, focusing on the limitations of traditional routing protocols under varying traffic conditions. The study introduces an improved version of the AODV protocol, termed Learning Automata-based AODV (LA-AODV), designed to enhance data transmission reliability and reduce latency. In this approach, LA-AODV utilizes location and movement information to optimize communication paths, adaptively selecting the most reliable routes based on real-time traffic dynamics. The objective is to evaluate LA-AODV’s performance against AODV based on metrics such as packet delivery, jitter, and end-to-end delay. The study assesses protocols in dynamic urban and highway traffic settings through quantitative simulations. Results indicate that LA-AODV consistently outperforms AODV, reducing jitter by 15% and increasing packet delivery by 12% in urban scenarios while decreasing end-to-end delay by 10% on highways. These gains are achieved by LA-AODV’s enhanced route selection, which incorporates location-based decisions for optimal communication paths. The study’s findings substantiate the reliability of LA-AODV, which is a significant step forward in the field of V2V communication. This research provides a foundation for advancing next-generation V2V communication systems in urban and highway contexts, instilling confidence in the potential of LA-AODV to improve V2V communication efficiency.

Analisis User Experience Website Sibela Proses Stock Opname di PT Bank Mandiri dengan Metode User Experience Questionnaire Cabang Plaza Mandiri dan Sudirman Jakarta Zaenudin, Muhamad Ridwan; Syahputra, Ade; Bintoro, Ketut Bayu Yogha
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2025: SNESTIK V
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2025.7263

The problem of card discrepancies during stocktaking is complicated for companies. The use of website inventory helps minimize the difference. The stock-taking process is also important in managing card stock at PT Bank Mandiri. However, some employees are reluctant to help with card data collection during sales. Users feel burdened by additional work and complicated applications, so they need to learn first to help with inventory. Therefore, user experience is an important factor. This study analyzes how users perceive and interact with the 'Sibela' website in overcoming card discrepancies during stock-taking. Data was collected through questionnaires using the Slovin method. The conclusion of the study shows that the clarity and novelty aspects of the SIBELA website scored lower than other aspects. Users had difficulty understanding the layout, navigation or information presented and felt the design or features were less relevant. Improvements need to focus on increasing the clarity of the interface, presenting information in a more structured manner, intuitive navigation, and updating designs and features to make them more modern and in line with technological trends. This step is expected to improve the user experience, so that the SIBELA website is more effective in supporting stock-taking.

Optimizing Connected Vehicle Routing Protocol for Smart Transportation Systems Bonari, Anggiet Harjo Baskoro; Bintoro, Ketut Bayu Yogha
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 2, May 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i2.2118

The significant growth in integrating connected vehicles into intelligent transportation networks has underscored the importance of Vehicle-to-Vehicle (V2V) communication in optimizing route efficiency, reducing traffic congestion, and enhancing road safety. However, routing protocols such as AODV face substantial challenges in dynamic automotive environments characterized by high mobility and rapid topology changes, leading to issues like packet loss, delays, and network congestion. Reactive protocols like AODV often suffer from route discovery delays, while proactive protocols like DSDV, although reducing latency, increase bandwidth consumption, making them less effective in highly dynamic contexts. This study introduces the Learning Automata Ad Hoc On-Demand (LA-AODV) routing protocol, designed to improve relay node selection and V2V communication efficiency. The proposed method leverages real-time vehicle data to predict and select optimal relay nodes under dynamic traffic conditions, thereby enhancing packet delivery ratio, throughput, and reducing latency and routing overhead. The results demonstrate that LA-AODV significantly outperforms AODV and DSDV across various traffic scenarios, with an increase in packet delivery ratio up to 4% in high traffic conditions, throughput reaching 125 units, and a reduction in end-to-end delay within the range of 2E+10 to 6E+14. These improvements highlight LA-AODV's superior efficiency in handling packet loss and latency, making it a suitable protocol for data-intensive and safety-critical applications that demand reliable and efficient data transmission. This study contributes by developing the LA-AODV protocol, which significantly enhances V2V communication performance in dynamic traffic scenarios and provides a robust simulation model replicating real-world conditions, potentially reducing traffic accidents.

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