UHEE-MAC: A Hybrid Emergency-Enabled MAC Protocol for the Internet of Underwater Things

Concerning the IoUT operating hybrid tasks, we introduce UHEE-MAC, an efficient MAC protocol that can enable quick emergency access as a sensor node switches from a non-emergency task to an emergency task and still supports a high throughput for non-emergency tasks. This efficiency stems from exploiting the long propagation delay to aggregate the interferences at each sensor node while aligning the packets at the receiving end. Whereas other related works are limited to reserving the time or frequency resource for direct access or obtaining channel control, respectively, which undoubtedly degrades the network throughput and increases the access delay. We discover that each sensor node experiences multiple and intermittent “deaf” periods when it cannot receive the necessary notification message to switch tasks. However, our analysis demonstrates that emergency access can be secured with at most two notifications if the “deaf” period is less than half the scheduling frame length. We then propose the detailed UHEEMAC, which does not require time synchronization in both the initialization and transmission stages. NS-3 simulations show UHEE-MAC outperforms PR-MAC and EE-MAC with $43.2 \%$ and 13.8% higher throughput, respectively. Emergency access delay is reduced to $24 \%$ of PR-MAC and 29% of EE-MAC, establishing superior hybrid task support capability.

Authors

Institutions

Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11148746
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

UHEE-MAC: A Hybrid Emergency-Enabled MAC Protocol for the Internet of Underwater Things

Quansheng Guan, Fei Ji, Shangguang Wang, Fangjiong Chen et al.
1 links
Underwater Vehicles and Communication Systems
article

UHEE-MAC: A Hybrid Emergency-Enabled MAC Protocol for the Internet of Underwater Things

Quansheng Guan, Fei Ji, Shangguang Wang, Fangjiong Chen, Hua Yu, Yan Wang
article en

Abstract

Concerning the IoUT operating hybrid tasks, we introduce UHEE-MAC, an efficient MAC protocol that can enable quick emergency access as a sensor node switches from a non-emergency task to an emergency task and still supports a high throughput for non-emergency tasks. This efficiency stems from exploiting the long propagation delay to aggregate the interferences at each sensor node while aligning the packets at the receiving end. Whereas other related works are limited to reserving the time or frequency resource for direct access or obtaining channel control, respectively, which undoubtedly degrades the network throughput and increases the access delay. We discover that each sensor node experiences multiple and intermittent “deaf” periods when it cannot receive the necessary notification message to switch tasks. However, our analysis demonstrates that emergency access can be secured with at most two notifications if the “deaf” period is less than half the scheduling frame length. We then propose the detailed UHEEMAC, which does not require time synchronization in both the initialization and transmission stages. NS-3 simulations show UHEE-MAC outperforms PR-MAC and EE-MAC with $43.2 \%$ and 13.8% higher throughput, respectively. Emergency access delay is reduced to $24 \%$ of PR-MAC and 29% of EE-MAC, establishing superior hybrid task support capability.

South China University of Technology (CN)
Openalex Percentile: Top 70%
Underwater Vehicles and Communication Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.