Green and Energy Monitoring for Future Network Infrastructures enabling also Large Deployments (GREENFIELD)

Partner	Infosim GmbH & Co. KG Städtische Werke Überlandwerke Coburg (SÜC) GmbH Associated Partner: Bechtle GmbH & Co. KG, IT-Systemhaus Regensburg
Funded Period	Januar 2024 – December 2026
Funder	BayVFP Förderlinie Digitalisierung „Informations- und Kummunikationstechnologie“
Researcher	Prof. Dr. Tobias Hoßfeld Dr. Frank Loh Noah Mehling M.Sc.

Project Description

The massive number of physical and virtual end devices in wired and wireless networks for undustrial use of smart city developments is causing an ever increasing energy consumption and environmental impact. Ecological sutstainability needs tob e a native concept in networking, in spite of the promise of a sustainable future promised by 6G and future networking technologies. Sustainability in the context of communication networks is difficult to grasp and quantify, especially, if a tradeoff between service quality and energy consumption is present.

This project aims to define and measure energy efficiency and ecological sustainability for communication networks and assess the potential optimizations in existing networks and application scenarios. The results from GREENFIELD will help to measure energy efficiency and sustainability to support automated solutions and decision making. In GREENFIELD, we address culturally relevant aspects of sustainability and research possible solutions for the real world.

The partners, Infosim GmbH & Co. KG, Städtische Überlandwerke Coburg GmbH (SÜC) and Chair of Communication Networks address these problems by combining their particular expertise. Infosim is well versed in network management, SÜC specializes in network expansion and operation, while the Chair of communication networks address the performance monitoring of network quality and sustainability.

Press report for the project start (german)

Project Objectives

Sustainability definition

Defining sustainability regarding CO2 consumption and efficiency
Measuring approach for sustainability

Model development

Develop models for sustainability, using measurable and context parameters
Ensuring model validation and explainability

Green monitoring and management architecture

Developing an architecture to support green monitoring
Integration with standardization efforts and existing protocols

Evaluation of the architecture

Performance modeling regarding accuracy of the monitoring and cost/benefit analysis regarding sustainability
Demonstration based on applicable use cases

Related Publications

Plan the Access? Generic Hardware Independent Energy Consumption and Efficiency Model for Different LoRaWAN Channel Access Approaches. Loh, Frank; Raffeck, Simon; Geißler, Stefan; Hoßfeld, Tobias. In IEEE Internet of Things Journal. 2024.
- [ BibTeX ]
- [ EndNote ]
@article{info3-article-2024-3, author = {Loh, Frank and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, journal = {IEEE Internet of Things Journal}, keywords = {sys:hidden:article}, month = {02}, title = {Plan the Access? Generic Hardware Independent Energy Consumption and Efficiency Model for Different LoRaWAN Channel Access Approaches}, year = 2024 }

%0 Journal Article %1 info3-article-2024-3 %A Loh, Frank %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %D 2024 %J IEEE Internet of Things Journal %T Plan the Access? Generic Hardware Independent Energy Consumption and Efficiency Model for Different LoRaWAN Channel Access Approaches
Analysis of Energy Intensity and Generic Energy Efficiency Metrics in Communication Networks: Limits, Practical Applications, and Case Studies. Hossfeld, Tobias; Wunderer, Stefan; Loh, Frank; Schien, Daniel. In IEEE Access, 12, pp. 105527–105549. 2024.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Energy intensity is the ratio between energy consumed and data volume over a certain time frame. It is frequently used as a metric to indicate the energy efficiency of communication networks and data centres for the provision of digital services, and as a coefficient to apportion the total energy consumption of a network to a specific service. As energy efficiency becomes more important, energy intensity metrics are increasingly used to estimate the energy costs and benefits of changes in data volumes across networks and data centres. Typically, energy intensity integrates annual accounts of energy consumption and data transmitted. At shorter time scales, this metric is affected by the lack of correlation between transmitted data and energy consumption, which leads in some cases to inappropriate conclusions. In this work, we first review the use of energy efficiency metrics in the literature. Then, we define generic measures for energy efficiency as well as energy intensity. The relationships of those measures are analysed, and we show under which conditions they lead to the same or different results. Practical applications of the measures and their insights are demonstrated when benchmarking systems and when considering the value of the system’s output. Furthermore, the limits and pitfalls of the metrics are analysed, especially considering the energy intensity metric for communication networks.

@article{10614603, abstract = {Energy intensity is the ratio between energy consumed and data volume over a certain time frame. It is frequently used as a metric to indicate the energy efficiency of communication networks and data centres for the provision of digital services, and as a coefficient to apportion the total energy consumption of a network to a specific service. As energy efficiency becomes more important, energy intensity metrics are increasingly used to estimate the energy costs and benefits of changes in data volumes across networks and data centres. Typically, energy intensity integrates annual accounts of energy consumption and data transmitted. At shorter time scales, this metric is affected by the lack of correlation between transmitted data and energy consumption, which leads in some cases to inappropriate conclusions. In this work, we first review the use of energy efficiency metrics in the literature. Then, we define generic measures for energy efficiency as well as energy intensity. The relationships of those measures are analysed, and we show under which conditions they lead to the same or different results. Practical applications of the measures and their insights are demonstrated when benchmarking systems and when considering the value of the system’s output. Furthermore, the limits and pitfalls of the metrics are analysed, especially considering the energy intensity metric for communication networks.}, author = {Hossfeld, Tobias and Wunderer, Stefan and Loh, Frank and Schien, Daniel}, journal = {IEEE Access}, keywords = {sys:hidden:article}, pages = {105527-105549}, title = {Analysis of Energy Intensity and Generic Energy Efficiency Metrics in Communication Networks: Limits, Practical Applications, and Case Studies}, volume = 12, year = 2024 }

%0 Journal Article %1 10614603 %A Hossfeld, Tobias %A Wunderer, Stefan %A Loh, Frank %A Schien, Daniel %D 2024 %J IEEE Access %P 105527-105549 %R 10.1109/ACCESS.2024.3435716 %T Analysis of Energy Intensity and Generic Energy Efficiency Metrics in Communication Networks: Limits, Practical Applications, and Case Studies %V 12 %X Energy intensity is the ratio between energy consumed and data volume over a certain time frame. It is frequently used as a metric to indicate the energy efficiency of communication networks and data centres for the provision of digital services, and as a coefficient to apportion the total energy consumption of a network to a specific service. As energy efficiency becomes more important, energy intensity metrics are increasingly used to estimate the energy costs and benefits of changes in data volumes across networks and data centres. Typically, energy intensity integrates annual accounts of energy consumption and data transmitted. At shorter time scales, this metric is affected by the lack of correlation between transmitted data and energy consumption, which leads in some cases to inappropriate conclusions. In this work, we first review the use of energy efficiency metrics in the literature. Then, we define generic measures for energy efficiency as well as energy intensity. The relationships of those measures are analysed, and we show under which conditions they lead to the same or different results. Practical applications of the measures and their insights are demonstrated when benchmarking systems and when considering the value of the system’s output. Furthermore, the limits and pitfalls of the metrics are analysed, especially considering the energy intensity metric for communication networks.