MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs

Area of Science:

• Wireless Sensor Networks (WSNs)
• Network topology
• Distributed algorithms

Background:

• Hierarchical clustering improves data fusion and energy efficiency in WSNs.
• Existing backbone construction algorithms (HCDD, MMM) suffer from rapid energy depletion.
• Lack of consideration for node residual energy and degree leads to network instability.

Purpose of the Study:

• To propose a stable backbone tree construction algorithm for WSNs.
• To enhance network lifetime and reduce energy consumption.
• To improve upon existing clustering schemes by considering node energy and connectivity.

Main Methods:

• A distributed algorithm for stable backbone construction using multi-hop clusters.
• Selection of cluster heads based on higher residual energy and node degree.
• Traffic load balancing around cluster heads to distribute energy consumption.

Main Results:

• The proposed algorithm creates a stable backbone by selecting energy-rich and well-connected nodes.
• Improved network lifetime compared to previous methods.
• Balanced energy consumption across nodes, reducing premature network disconnection.

Conclusions:

• The proposed algorithm offers a more stable and energy-efficient backbone construction for WSNs.
• Considering residual energy and node degree is crucial for long-term network viability.
• This approach enhances overall WSN performance and longevity.