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Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Distributed power allocation for sink-centric clusters in multiple sink wireless sensor networks.

Lei Cao¹, Chen Xu, Wei Shao

¹Department of Electronic and Information, The University of Nantong, Nantong Jiangsu, China.

Sensors (Basel, Switzerland)

|February 2, 2012

Summary

This study introduces a new energy-saving protocol for wireless sensor networks (WSNs) using multiple sinks and adaptive clustering. The proposed Multiple Sink Cluster Wireless Sensor Networks with Power Control (MSCWSNs-PC) optimizes network topology for efficiency.

Keywords:

clustering hierarchy multiple sink power control sensor networks wireless communication

Related Experiment Videos

Last Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Computer Science
Electrical Engineering
Network Engineering

Background:

Energy conservation is critical in large-scale wireless sensor networks (WSNs) due to battery limitations.
Existing solutions include deploying multiple sink nodes or using adaptive clustering hierarchy routing.
A combined approach can potentially enhance network efficiency and longevity.

Purpose of the Study:

To propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink WSNs.
To develop a distributed, scalable, self-organizing, and adaptive system for WSNs.
To optimize network topology through power control in a multi-sink environment.

Main Methods:

Developed a novel protocol named MSCWSNs-PC, integrating multiple sinks and adaptive clustering.
Implemented a transmission power control scheme for sink-centric cluster routing.
Designed a system where sensor nodes do not require global network or location awareness.
Utilized simulations to evaluate the protocol's performance.

Main Results:

The proposed MSCWSNs-PC protocol effectively manages energy consumption in WSNs.
The system demonstrates scalability, self-organization, and adaptability.
Power control optimizes the network topology for improved performance.
Simulations confirmed the protocol's advantages over existing methods.

Conclusions:

The MSCWSNs-PC protocol offers a viable solution for energy saving in large WSNs.
Combining multiple sinks with adaptive clustering and power control enhances network efficiency.
The protocol's distributed and adaptive nature makes it suitable for complex WSN deployments.