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All Journal KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Bintoro, Ketut Bayu
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Computer Science & IT Decision Sciences, Operations Research & Management

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Analisis Simulasi Routing AODV Adaptif dengan Learning Automata untuk Komunikasi V2V Effendi, Muhamad Denhas; Bintoro, Ketut Bayu; Widyaningsih, Maura
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 15 No 1 (2025): Maret 2025
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v15i1.820

Abstract

The study addresses the limitations of the Ad Hoc On-Demand Distance Vector (AODV) protocol in vehicle-to-vehicle (V2V) communication, explicitly targeting issues such as low data transfer rates, increased delay times, reduced throughput, and data congestion due to dynamic network topologies. The research introduces a novel protocol called Learning Automata Ad Hoc On-Demand (LAAODV) to enhance these areas. Utilizing NS3 and SUMO for dynamic traffic simulations, LAAODV demonstrated superior performance compared to AODV. Key findings include a higher packet delivery success rate with a Packet Loss Ratio (PLR) of 95%, lower than AODV's 96%, and a Packet Delivery Ratio (PDR) of 4.5% compared to AODV's 3.25%, indicating its effectiveness in reducing packet loss. The study also highlights significant improvements in PDR and Average Throughput, showcasing LAAODV's enhanced performance in dynamic traffic conditions. LAAODV provides an effective solution to the shortcomings of existing routing protocols, significantly enhancing V2V network performance. This research underscores the importance of developing robust and adaptive routing solutions to meet the evolving demands of dynamic vehicular environments, contributing to more efficient and reliable V2V communication protocols.
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

Abstract

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.
Co-Authors Effendi, Muhamad Denhas Ketut Bayu Yogha Bintoro Letsoin, Fita Sari Maura Widyaningsih, Maura Sadiah, Hanna Halimatu