Energy and Load Balanced Multi-Gateway Selection Strategy

To address the challenges of energy consumption, load congestion, and scheduling imbalance in sea surface wireless mesh networks, this paper proposes an Energy and Load Balanced Gateway Selection (ELB-GS) strategy-a dynamic multi-gateway selection method. ELB-GS integrates node residual energy and MAC queue occupancy into a composite QoS metric, enabling source nodes to adaptively choose optimal gateways through periodic sensing. Simulations on the NS-3 platform under typical sea conditions demonstrate that ELB-GS outperforms the traditional static strategy Zonal Gateway Selection (ZGS) in packet delivery, throughput, and load balancing. Although it introduces a slight increase in delay, ELB-GS improves transmission stability and energy efficiency, demonstrating its effectiveness and robustness in marine environments.

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Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/iccsn66511.2025.11172471
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
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Energy and Load Balanced Multi-Gateway Selection Strategy

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Energy Efficient Wireless Sensor Networks
article

Energy and Load Balanced Multi-Gateway Selection Strategy

Yuhan Yao, J. Wang, Jiaqi Cui, Yan Zhang, Tingting Lyu
article en

Abstract

To address the challenges of energy consumption, load congestion, and scheduling imbalance in sea surface wireless mesh networks, this paper proposes an Energy and Load Balanced Gateway Selection (ELB-GS) strategy-a dynamic multi-gateway selection method. ELB-GS integrates node residual energy and MAC queue occupancy into a composite QoS metric, enabling source nodes to adaptively choose optimal gateways through periodic sensing. Simulations on the NS-3 platform under typical sea conditions demonstrate that ELB-GS outperforms the traditional static strategy Zonal Gateway Selection (ZGS) in packet delivery, throughput, and load balancing. Although it introduces a slight increase in delay, ELB-GS improves transmission stability and energy efficiency, demonstrating its effectiveness and robustness in marine environments.

Ocean University of China (CN)
Openalex Percentile: Top 70%
Energy Efficient Wireless Sensor Networks
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