Table 1 Comparative summary of existing clustering and routing approaches.

From: Energy-efficient clustering and routing for IoT-enabled healthcare using adaptive fuzzy logic and hybrid optimization

Method/Reference

Advantages

Limitations

FCM + PSO + GA26

Improved CH distribution and energy balancing

High computational overhead, not real-time friendly

Swarm Intelligence in IoMT27

Adaptive, decentralized decision-making

Lacks clarity on real-time scalability and resource use

SI + CNN-LSTM IDS28

High intrusion detection accuracy

High complexity, limited adaptive learning

PSO + Deep Learning29

Enhanced routing and energy saving

Complex integration, not optimal for low-resource SNs

ANFIS Health Monitoring30

High anomaly detection, adaptability

Resource-heavy, not ideal for large-scale streaming

GA + PSO + RF31

High prediction accuracy for heart disease

Focused on diagnosis, not routing or CH optimization

QPSO + Fuzzy Logic32

Extended network life, improved stability

Computational complexity increases in real-time scenarios

PSO + Fuzzy Clustering33

Balanced energy usage, improved delivery

Reduced efficiency in large-scale networks