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Related Experiment Video

Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

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

Published on: September 8, 2023

Evolutionary optimization for energy efficient service provisioning in IT and optical network infrastructures.

Markos P Anastasopoulos1, Anna Tzanakaki, Konstantinos Georgakilas

  • 1Athens Information Technology, 19.5km Markopoulou Ave., Peania, Athens, GR - 19002, Greece.

Optics Express
|January 26, 2012
PubMed
Summary

This study introduces an energy-efficient service provisioning method for combined IT and optical networks. The novel evolutionary distributed approach achieves performance comparable to traditional centralized methods.

Related Experiment Videos

Last Updated: May 25, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

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

Published on: September 8, 2023

Area of Science:

  • Computer Science
  • Telecommunications Engineering
  • Network Optimization

Background:

  • Integrated IT and optical networks present unique challenges for energy-efficient service provisioning.
  • Optimizing resource allocation in these hybrid infrastructures is crucial for reducing operational costs and environmental impact.

Purpose of the Study:

  • To develop and evaluate a novel evolutionary distributed approach for energy-efficient service provisioning in integrated IT and optical network infrastructures.
  • To compare the performance of the proposed approach against established Integer Linear Programming (ILP) based centralized methods.

Main Methods:

  • A novel evolutionary distributed algorithm was designed for service provisioning.
  • The proposed algorithm was implemented and simulated within an integrated IT and optical network environment.
  • Performance was evaluated based on energy consumption and service delivery metrics.

Main Results:

  • The evolutionary distributed approach demonstrated comparable performance to ILP-based centralized methods in terms of energy efficiency.
  • Modeling results indicated that the proposed approach can effectively manage resources in hybrid network infrastructures.
  • The distributed nature of the approach offers potential scalability benefits.

Conclusions:

  • Energy-efficient service provisioning in integrated IT and optical networks can be effectively achieved using evolutionary distributed algorithms.
  • The proposed approach provides a viable alternative to centralized methods, potentially offering advantages in scalability and resilience.
  • Further research can explore the application of this approach in dynamic network scenarios.