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Updated: Jun 23, 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 consensus filtering in sensor networks.

Wenwu Yu¹, Guanrong Chen, Zidong Wang

¹Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. wenwuyu@gmail.com

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|May 19, 2009

Summary

This summary is machine-generated.

This study introduces novel distributed consensus filters for sensor networks, enabling efficient data processing through neighbor communication. The pinning control approach allows network-wide control with minimal sensor measurements, even with partial information.

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Area of Science:

Control Engineering
Networked Systems
Signal Processing

Background:

Sensor networks require robust filtering for accurate data acquisition.
Distributed filtering offers scalability and resilience compared to centralized approaches.
Existing methods may struggle with partial observability or limited communication.

Purpose of the Study:

To investigate a new filtering problem in sensor networks.
To design novel distributed consensus filters.
To address filtering under partial target information using pinning observers.

Main Methods:

Development of distributed consensus filters enabling neighbor communication.
Application of pinning control strategies where only a subset of sensors measure target information.
Design of pinning observers for scenarios with partial sensor observability.

Main Results:

Successful design of distributed consensus filters verified through simulations.
Demonstration of effective network control using a small fraction of sensors (pinning control).
Validation of pinning observers for handling partial target information.

Conclusions:

The proposed distributed consensus filters are effective for sensor networks.
Pinning control and observers provide efficient solutions for distributed filtering, even with partial information.
Simulation results confirm the practical applicability of the developed methods.