HERMEES: A Holistic Evaluation and Ranking Model for Energy-Efficient Systems Applied to Selecting Optimal...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Security

Background:

• Wireless Sensor Networks (WSNs) require efficient algorithm selection for optimal performance.
• Balancing energy efficiency, security, and network topology is crucial for WSN deployment.
• Existing models may lack adaptability to diverse operational scenarios and user requirements.

Purpose of the Study:

• To present HERMEES (Holistic Evaluation and Ranking Model for Energy Efficient Systems).
• To develop a multi-criteria decision-making (MCDM) framework for selecting optimal Lightweight Cryptography (LWC) and Topology Construction Protocol (TCP) algorithm combinations for WSNs.
• To enable WSNs to be configured for specific user-defined scenarios and operational needs.

Main Methods:

• Utilized a Multi-Criteria Decision-Making (MCDM) model.
• Employed the Simple Additive Weighting (SAW) method for scoring algorithm pairs based on weighted criteria.
• Applied mean shift clustering to group and identify top-performing algorithm combinations.
• Evaluated the model using a scenario in a medium-sized agricultural field.

Main Results:

• The HERMEES model successfully identified optimal LWC and TCP algorithm combinations for the tested WSN scenario.
• The SAW method effectively assigned scores based on scenario-specific criteria weighting.
• Mean shift clustering refined the selection process, highlighting the best-suited algorithm pairs.
• The model demonstrated versatility and adaptability for WSN configuration.

Conclusions:

• HERMEES provides a robust framework for selecting energy-efficient algorithms in WSNs.
• The model supports the development of guided, self-configuring, context-aware WSNs.
• This approach enables dynamic adaptation of WSNs to various application requirements and operational contexts.