A novel topology control approach to maintain the node degree in dynamic wireless sensor networks

Area of Science:

• Computer Science
• Network Engineering
• Wireless Communication

Background:

• Topology control is crucial for Wireless Sensor Network (WSN) connectivity and reliability.
• Existing methods often require location information or complex rule design.

Purpose of the Study:

• Propose a novel Fuzzy-logic Topology Control (FTC) algorithm.
• Achieve a desired average node degree by adaptively adjusting communication range.
• Improve WSN connectivity and reliability without location data.

Main Methods:

• Developed a fully localized control algorithm (FTC).
• Constructed the fuzzy-logic controller from training data, avoiding explicit membership functions and rules.
• Evaluated FTC through extensive simulations against NONE, FLSS, k-Neighbor, and LTRT algorithms.

Main Results:

• FTC effectively achieves the desired average node degree across varying node densities, similar to the k-Neighbor algorithm.
• FTC demonstrates comparable energy efficiency to FLSS and k-Neighbor, outperforming LTRT and NONE.
• FTC achieves the lowest average maximum communication range, indicating reduced power consumption for the most energy-intensive nodes.

Conclusions:

• FTC is an accurate, stable, and efficient topology control algorithm for WSNs.
• The data-driven approach simplifies FTC design and implementation.
• FTC offers significant improvements in achieving target connectivity and energy efficiency.