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Related Experiment Video

Updated: May 26, 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

Deployment of distributed applications in wireless sensor networks.

Virginia Pilloni¹, Luigi Atzori

¹Department of Electric and Electronic Engineering, University of Cagliari, Cagliari 09123, Italy. virginia.pilloni@diee.unica.it

Sensors (Basel, Switzerland)

|December 14, 2011

Summary

This study introduces a novel framework for deploying applications on wireless sensor networks (WSN). It optimizes task allocation to conserve energy, outperforming traditional methods, especially in dense networks.

Keywords:

Wireless Sensor Networks energy consumption network lifetime

Related Experiment Videos

Last Updated: May 26, 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
Ubiquitous Computing

Background:

Advancements in Wireless Sensor Network (WSN) nodes, including computation, sensing, and battery life, enable ambient intelligence infrastructures.
Programmable middleware facilitates rapid deployment of diverse applications on WSNs to meet evolving ambient needs.

Purpose of the Study:

To address the challenge of deploying applications on complex WSNs with hundreds of nodes.
To minimize the impact of application execution on the WSN infrastructure's battery lifetime.

Main Methods:

Developed a framework that considers all possible task decompositions for sensing and computing operations across WSN nodes.
Incorporated energy consumption of each task into a cost function to evaluate deployment solution viability.

Main Results:

The proposed framework significantly conserves energy compared to sink-oriented or cluster-oriented deployment strategies.
Effectiveness is particularly pronounced in networks with high node density, non-uniform energy distribution, and complex application actions.

Conclusions:

The developed framework offers an energy-efficient solution for application deployment in complex WSN environments.
Optimized task allocation is crucial for extending the operational lifetime of WSNs in ambient intelligence applications.