REAL

Energy-efficient threshold-based reinforcement learning for WSN routing

Chaudhari, Archana and Abdullah, Masuk and Deshpande, Vivek and Midhunchakkaravarthy, Divya (2026) Energy-efficient threshold-based reinforcement learning for WSN routing. POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES, 21 (2). pp. 64-70. ISSN 1788-1994

[img]
Preview
Text
606-article-p64.pdf - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

The proposed method uses a threshold-based reinforcement learning algorithm, Q-learning, for efficient routing in wireless sensor networks. It penalizes node energy, hop count, and distance to sink using three key thresholds to select the next best forwarder. This prevents self-loops and ensures packet delivery by avoiding low energy or high hop count nodes. The combination of reinforcement learning and key threshold values allows intelligent data packet routing, handling congestion near sink nodes, and reliable transmission. Experimental results show a 35% enhanced network lifetime compared to the state-of-the-art algorithm.

Item Type: Article
Uncontrolled Keywords: wireless sensor networks, threshold-based Q-routing, hop count, node energy, sink
Subjects: T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 31 Jul 2026 11:17
Last Modified: 31 Jul 2026 11:17
URI: https://real.mtak.hu/id/eprint/243658

Actions (login required)

Edit Item Edit Item