Enhancing Clustering Efficiency in Heterogeneous Wireless Sensor Network Protocols Using the K-Nearest Neighbours...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) are critical for data collection but face challenges with energy consumption and network lifespan.
• Effective clustering protocols are essential for secure connections and stable network lifetime in WSNs.
• Existing protocols like LEACH, SEP, TEEN, and DEC have limitations in energy efficiency and connection optimization.

Purpose of the Study:

• To introduce a novel K-Nearest Neighbours (KNN) algorithm for optimizing node selection and clustering in WSNs.
• To improve energy efficiency, reduce network connection lengths, and extend the operational lifetime of heterogeneous WSNs.
• To evaluate the efficacy of the KNN algorithm in enhancing four established WSN protocols: LEACH, SEP, TEEN, and DEC.

Main Methods:

• Implementation of the K-Nearest Neighbours (KNN) algorithm to optimize clustering mechanisms within WSN protocols.
• Modification and simulation of four distinct WSN protocols (LEACH, SEP, TEEN, DEC) using the proposed KNN approach.
• Performance evaluation through MATLAB simulations focusing on energy consumption, connection distances, and network lifetime.

Main Results:

• The KNN-optimized protocols demonstrated shorter distances between cluster heads and sensor nodes.
• Significant reductions in overall energy consumption were observed across the modified protocols.
• The proposed KNN-based approach led to a notable increase in the overall network lifetime.
• Enhanced network operational efficiency and security were achieved through optimized clustering.

Conclusions:

• The K-Nearest Neighbours (KNN) algorithm offers a robust and effective solution for energy management in Wireless Sensor Networks.
• Optimizing node selection and clustering with KNN significantly improves key performance metrics in WSNs.
• The proposed method provides a valuable enhancement for heterogeneous WSNs, extending their practical applicability and lifespan.