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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Information System Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal E-Komtek Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Sistem Informasi Galuh
Firmansyah, Muhammad Raafi'u
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Journal : Indonesian Journal of Information System

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Adaptive Integration of Distributed Deep Q-Networks for Enhancing OLSR Routing in Dynamic Mobile Ad-Hoc Networks Tirta Segara, Alon Jala; Bahtiar, Arief Rais; Firmansyah, Muhammad Raafi'u; Wibowo, Fahrudin Mukti
Indonesian Journal of Information Systems Vol. 8 No. 2 (2026): February 2026
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i2.11760

Abstract

Adaptive routing in Mobile Ad-Hoc Networks (MANETs) poses considerable difficulty owing to the network's dynamic characteristics, lack of stable infrastructure, and swift topology alterations. The Optimized Link State Routing (OLSR) protocol provides a proactive routing mechanism via topology dissemination and MultiPoint Relay (MPR) selection. Nevertheless, it exhibits diminished responsiveness to real-time topology alterations, as it depends on periodic updates and does not explicitly account for link quality. This paper suggests the incorporation of the Deep Q-Network (DQN) methodology into OLSR as a reinforcement learning strategy to improve routing adaptability and efficiency. The DQN model employs network metrics like latency, ETX, buffer occupancy, and neighbor count as state inputs, with actions determined by Q-values obtained via environmental interactions. Simulations conducted with NS-3 and PyTorch demonstrate that OLSR-DQN enhances Packet Delivery Ratio (PDR) by as much as 20%, decreases delay by 15–25%, and markedly boosts throughput in dynamic MANET situations. Keywords: MANET, OLSR, Deep Q-Network, adaptive routing, reinforcement learning
Co-Authors Adanti Wido Paramadini Arief Rais Bahtiar Dasril Aldo Dedi Rahman Habibie Faiz, M. Hanif Al Fathan, Faizal Burhani Ulil Fau, Andrew Gusla Nengsih, Yeyi Hidayat, Afifah Naurah Lina Fatimah Lishobrina Lisda Lisda M Yoka Fathoni Maulana, Ihsan Muadin, Dika Alim Muhammad Afrizal Amrustian Nenen Isnaeni Sa'adah, Aminatus Sahara Sahara Sulaeman, Gilang Suprapto, Amelia Rut Tirta Segara, Alon Jala Utami, Annisaa Wibowo, Fahrudin Mukti Yasin, Feri Yohani Setiya Rafika Nur