Page 11 - TECH MAGAZINE CSE

AN Technical Magazine
VESHAN Maharaja Agrasen Institute of Technology

FACULTY
CORNER Ashish Sharma, Assistant Professor, CSE

Department of Computer Science &

Engineering

Advancements in Cluster Head Selection and Cluster Formation

Methods in Wireless Sensor Networks: A Review

Wireless Sensor Networks (WSNs) are widely used in areas like environmental

monitoring and healthcare but face challenges such as limited energy and
short communication ranges. Clustering, where nodes are grouped and a
cluster head (CH) is elected, helps manage resources efficiently. Effective CH
selection is key to avoiding energy drain and improving network lifetime.

Advancements in CH Selection
Recent research in 2024 focuses on hybrid metaheuristic algorithms, like
combining Genetic Algorithms (GA) with Particle Swarm Optimization (PSO), for
better CH selection. Energy-aware methods, such as the fuzzy-based FEECA

approach, also enhance network stability by prioritizing nodes with higher
residual energy.
Advancements in Cluster Formation
Improved cluster formation methods like unequal clustering and K-means are

being enhanced. New techniques such as the Hybrid Optimal-Based Cluster
Formation (HOBCF) and grid-based clustering use energy and location metrics
to optimize cluster structure and extend network life.
Open Issues & Future Directions

Challenges remain in developing adaptive and secure clustering methods for
dynamic networks. Future research aims to integrate deep learning and
lightweight algorithms for smarter and more efficient WSN management.

Conclusion
2024 research has significantly advanced CH selection and cluster formation
in WSNs, improving energy efficiency and stability. Ongoing work will focus on
making these systems more adaptive, secure, and intelligent.