Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless sensor networks (WSNs) face significant energy constraints due to limited power capabilities of individual sensor nodes.
• Efficient energy utilization is critical for extending the operational lifetime of WSNs.

Purpose of the Study:

• To propose a novel energy-efficient clustering protocol for WSNs.
• To enhance the protocol for improved network performance metrics like throughput and delay.
• To ensure network stability, particularly in dynamic scenarios.

Main Methods:

• Development of the distance-based and low-energy adaptive clustering (DISCPLN) protocol.
• Enhancement of DISCPLN into multi-hop-DISCPLN for better throughput and reduced delay/packet loss.
• Introduction of mobile-DISCPLN to address network stability challenges.
• Comparative modeling and analysis against existing benchmark protocols.

Main Results:

• The proposed DISCPLN protocol demonstrates efficient energy utilization, addressing the 'green' computing challenge in WSNs.
• Multi-hop-DISCPLN shows significant improvements in network lifetime, characterized by high throughput and minimal delay and packet loss.
• Mobile-DISCPLN effectively maintains network stability.
• Modeling and benchmark comparisons indicate superior performance of the proposed protocols.

Conclusions:

• The DISCPLN family of protocols offers a viable solution for enhancing energy efficiency and extending the lifetime of wireless sensor networks.
• The enhanced protocols provide a robust framework for optimizing WSN performance under various operational conditions.
• The findings suggest a promising direction for the design of sustainable and high-performing WSNs.