A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks.

Area of Science:

• Computer Science
• Wireless Sensor Networks
• Network Protocols

Background:

• Wireless Sensor Networks (WSNs) face challenges in balancing energy consumption and data transmission latency.
• Existing methods often struggle to optimize both energy efficiency and low-latency data collection.

Purpose of the Study:

• To propose a novel low-latency data gathering method with multi-Sink (LDGM) for WSNs.
• To enhance energy efficiency and reduce end-to-end delay in WSN data transmission.

Main Methods:

• Dividing the WSN into virtual regions with a maximum of three data gathering units.
• Selecting regional leaders based on residual energy and distance to other nodes.
• Implementing sleep scheduling and sensing radius adjustment strategies to minimize coverage redundancy.
• Utilizing mobile sinks for data collection from regional leaders.

Main Results:

• LDGM demonstrates superior energy efficiency compared to Minimum Spanning Tree (MST) and Minimum Wireless Spanning Tree (MWST) methods.
• LDGM achieves higher time efficiency in data collection than single-sink methods.
• Reduced energy consumption and end-to-end delay were observed due to the multi-sink approach and leader-based communication.

Conclusions:

• LDGM effectively balances energy consumption and latency in WSNs.
• The proposed method offers significant improvements in both energy and time efficiency for data gathering.
• LDGM provides a viable solution for optimizing performance in resource-constrained WSN environments.