Home // SIMUL 2025, The Seventeenth International Conference on Advances in System Modeling and Simulation // View article
Authors:
Ozhan Eren
Aysegul Altin-Kayhan
Keywords: Simulation; spatial partitioning; underwater wireless sensor networks; traffic uncertainty; robust optimization
Abstract:
Underwater Wireless Sensor Networks (UWSNs) have attracted considerable attention for decades, owing to their broad spectrum of application areas. Despite technological advances, designing energy-efficient underwater communication architectures remains a key challenge due to the harsh and dynamic environment. Among the various factors influencing the performance of UWSNs, data traffic load emerges as a critical component, particularly in relation to the operational lifetime. Additionally, with their increasing deployment, Autonomous Underwater Vehicles (AUVs) are integrated into UWSNs in various roles. However, their presence introduces new challenges that require the design of robust sensor network configurations capable of effectively detecting and interacting with AUVs. This paper addresses a novel simulation-driven and uncertainty-aware design scheme for energy-efficient UWSNs. Building on prior studies of data traffic uncertainty in wireless sensor networks and AUV mobility, this paper employs a simulation environment that captures the integrated interactions among mobile targets, sensor nodes, and seabed topography to evaluate the proposed network model. Furthermore, recognizing that the unrestricted mobility of navigating vehicles can cause variations in data generation rates across the network, we apply balanced 3D K-means partitioning to structure the network for uncertainty modeling. The proposed robust optimization framework is evaluated against a deterministic baseline under varying traffic conditions induced by vehicle movement. To capture uncertainty at multiple scales, we incorporate parameters representing sensor-specific deviations and regional conservativeness, enabling examination of their impact on solution stability. Results indicate that the robust framework consistently outperforms the deterministic approach across varying levels of traffic deviation under the applied spatial partitioning scheme.
Pages: 88 to 94
Copyright: Copyright (c) IARIA, 2025
Publication date: September 28, 2025
Published in: conference
ISSN: 2308-4537
ISBN: 978-1-68558-300-2
Location: Lisbon, Portugal
Dates: from September 28, 2025 to October 2, 2025