Density-aware and energy-gradient based relay selection for enhanced routing in mobile sink wireless sensor networks

Wireless Sensor Networks (WSNs) are popular for monitoring purposes, but it is found that the networks' lifetime may be restricted by energy limitations and load imbalance. Therefore, the authors propose a new energy-balancing protocol called Density-Energy Gradient-based Relay Routing (DEGR) that combines local node density and residual energy gradients in order to choose relay nodes for the dynamic formation of optimal routing paths to maximize routing efficiency in mobile sink-enabled WSNs. In contrast to clustering protocols and static sector based routing, the DEGR dynamically determines the relay nodes which are not only energy abundant but also strategically located in dense areas, thus avoiding hotspots and extending network lifetime. DEGR combined with an adaptive clustering model and circular sink mobility, provides balanced distribution of energy and low latency delivery of data. The results of the simulations in MATLAB show that DEGR outperforms Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy-aware Clustering and Data Routing Algorithm (ECDRA), LEACH with Mobile Sink (MS-LEACH), and Mobility and Energy Adaptive Density-based Clustering (MEADC) protocols. It increases the lifespan of the first node death by approximately 54% compared to LEACH, decreases the variance of energy consumed by approximately 40%, and keeps the packet delivery ratio above 90% all the time. These results show the relative performance advantage of DEGR in the simulations in the specified simulation framework.

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Publication Details

Journal
Scientific Reports
Published
2026-06-16
DOI
https://doi.org/10.1038/s41598-026-57246-2
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
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article

Density-aware and energy-gradient based relay selection for enhanced routing in mobile sink wireless sensor networks

Idris H. Smaili, Ibrahim Aqeel, Emad S. Hassan, Ayman A. Alharbi
Scientific Reports
Energy Efficient Wireless Sensor Networks
article

Density-aware and energy-gradient based relay selection for enhanced routing in mobile sink wireless sensor networks

Idris H. Smaili, Ibrahim Aqeel, Emad S. Hassan, Ayman A. Alharbi
article en

Abstract

Wireless Sensor Networks (WSNs) are popular for monitoring purposes, but it is found that the networks' lifetime may be restricted by energy limitations and load imbalance. Therefore, the authors propose a new energy-balancing protocol called Density-Energy Gradient-based Relay Routing (DEGR) that combines local node density and residual energy gradients in order to choose relay nodes for the dynamic formation of optimal routing paths to maximize routing efficiency in mobile sink-enabled WSNs. In contrast to clustering protocols and static sector based routing, the DEGR dynamically determines the relay nodes which are not only energy abundant but also strategically located in dense areas, thus avoiding hotspots and extending network lifetime. DEGR combined with an adaptive clustering model and circular sink mobility, provides balanced distribution of energy and low latency delivery of data. The results of the simulations in MATLAB show that DEGR outperforms Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy-aware Clustering and Data Routing Algorithm (ECDRA), LEACH with Mobile Sink (MS-LEACH), and Mobility and Energy Adaptive Density-based Clustering (MEADC) protocols. It increases the lifespan of the first node death by approximately 54% compared to LEACH, decreases the variance of energy consumed by approximately 40%, and keeps the packet delivery ratio above 90% all the time. These results show the relative performance advantage of DEGR in the simulations in the specified simulation framework.

Scientific Reports
Umm al-Qura University (SA), Jazan University (SA)
Affordable and clean energy
Openalex Percentile: Top 4%
Energy Efficient Wireless Sensor Networks
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Density-aware and energy-gradient based relay selection for enhanced routing in mobile sink wireless sensor networks — Idris H. Smaili, Ibrahim Aqeel, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS