HERMEES: A Holistic Evaluation and Ranking Model for Energy-Efficient Systems Applied to Selecting Optimal Lightweight Cryptographic and Topology Construction Protocols in Wireless Sensor Networks

This paper presents HERMEES-Holistic Evaluation and Ranking Model for Energy Efficient Systems. HERMEES is based on a multi-criteria decision-making (MCDM) model designed to select the optimal combination of lightweight cryptography (LWC) and topology construction protocol (TCP) algorithms for wireless sensor networks (WSNs) based on user-defined scenarios. The proposed model is evaluated using a scenario based on a medium-sized agricultural field. The Simple Additive Weighting (SAW) method is used to assign scores to the candidate algorithm pairs by weighting the scenario-specific criteria according to their significance in the decision-making process. To further refine the selection, mean shift clustering is utilized to group and identify the highest scored candidates. The resulting model is versatile and adaptable, enabling WSNs to be configured according to specific operational needs. The provided pseudocode elucidates the model workflow and aids in an effective implementation. The presented model establishes a solid foundation for the development of guided self-configuring context-aware WSNs capable of dynamically adapting to a wide range of application requirements.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-04-25
DOI
https://doi.org/10.3390/s25092732
Citations
2
Primary Topic
Security in Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
2.97
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HERMEES: A Holistic Evaluation and Ranking Model for Energy-Efficient Systems Applied to Selecting Optimal Lightweight Cryptographic and Topology Construction Protocols in Wireless Sensor Networks

Dejan Drajić, Djordje Babić, Nemanja Radosavljevic, Petar Prvulović
2 citations
Sensors
Security in Wireless Sensor Networks
2.97
article

HERMEES: A Holistic Evaluation and Ranking Model for Energy-Efficient Systems Applied to Selecting Optimal Lightweight Cryptographic and Topology Construction Protocols in Wireless Sensor Networks

Dejan Drajić, Djordje Babić, Nemanja Radosavljevic, Petar Prvulović
article en
2 citations

Abstract

This paper presents HERMEES-Holistic Evaluation and Ranking Model for Energy Efficient Systems. HERMEES is based on a multi-criteria decision-making (MCDM) model designed to select the optimal combination of lightweight cryptography (LWC) and topology construction protocol (TCP) algorithms for wireless sensor networks (WSNs) based on user-defined scenarios. The proposed model is evaluated using a scenario based on a medium-sized agricultural field. The Simple Additive Weighting (SAW) method is used to assign scores to the candidate algorithm pairs by weighting the scenario-specific criteria according to their significance in the decision-making process. To further refine the selection, mean shift clustering is utilized to group and identify the highest scored candidates. The resulting model is versatile and adaptable, enabling WSNs to be configured according to specific operational needs. The provided pseudocode elucidates the model workflow and aids in an effective implementation. The presented model establishes a solid foundation for the development of guided self-configuring context-aware WSNs capable of dynamically adapting to a wide range of application requirements.

SensorsVol. 25(9)
University of Belgrade (RS), Union University (RS)
Openalex Percentile: Top 9%
Security in Wireless Sensor Networks
2.97
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.