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Related Experiment Video

Updated: Feb 17, 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

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Energy-aware virtual network embedding in flexi-grid networks.

Rongping Lin, Shan Luo, Haoran Wang

    Optics Express
    |December 10, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study addresses energy-aware virtual network embedding (VNE) in optical networks. A heuristic algorithm effectively minimizes electricity costs while maintaining high acceptance ratios for virtual network requests.

    Related Experiment Videos

    Last Updated: Feb 17, 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

    1.2K

    Area of Science:

    • Computer Science
    • Telecommunications Engineering
    • Network Optimization

    Background:

    • Network virtualization allows multiple virtual networks (VNs) on a shared substrate, improving resource utilization.
    • The virtual network embedding (VNE) problem, mapping VNs onto the substrate, is a significant challenge.
    • Energy efficiency is increasingly critical in network design for cost reduction and environmental sustainability.

    Purpose of the Study:

    • To address the energy-aware virtual network embedding (VNE) problem specifically within flexi-grid optical networks.
    • To minimize the electricity costs associated with processing each incoming VN request.
    • To develop a practical solution balancing performance and energy efficiency.

    Main Methods:

    • An integer linear programming (ILP) formulation was developed to model and optimize the energy-aware VNE problem.
    • A polynomial-time heuristic algorithm was proposed for sequential embedding of virtual links.
    • The heuristic algorithm was designed to maintain a reasonable VN acceptance ratio and minimize electricity costs.

    Main Results:

    • The proposed heuristic algorithm closely approximates the optimal solution provided by the ILP for smaller network instances.
    • The heuristic algorithm demonstrates scalability and applicability to larger, more complex network scenarios.
    • The study successfully balances the trade-offs between VN acceptance rates and energy consumption.

    Conclusions:

    • The developed heuristic algorithm offers an efficient and effective approach to solving the energy-aware VNE problem in flexi-grid optical networks.
    • This method provides a practical solution for reducing operational expenses and enhancing the ecological footprint of optical networks.
    • The findings support the deployment of energy-efficient network virtualization strategies in modern communication infrastructures.