Energy consumption measurements and optimization in mobile networks – ECOMOME

To address these objectives, we will conduct measurement campaigns on mobile networks, in a series of scenarios, covering the UE, the RAN and their interactions, using both open platforms and real operator networks. The results of this exhaustive experimental campaign will be made available to any interested party in an open data spirit.

Based on this experimental campaign, the ECOMOME project will define accurate energy consumption models for a mobile network. Instead of taking a generic approach and providing an average consumption per equipment, these models will focus on “atomic” mechanisms and functions of the mobile network, which can then be combined in order to provide information for a large number of services and scenarios.

Finally, we will develop new experimentally-validated energy consumption models for emerging virtualized mobile networks which will cover the entire range of the foreseeable scenarios that future generation of mobile networks will pose, proposing innovative NI-based solutions towards an energy-efficient RAN.

For now, we conducted a wide series of measurements, using both software-based and hardware-based solutions. The hardware-based measurement platform is operational, and it has been used to collect data for numerous scenarios, including network attachment, Internet access, SMS transmission, SMS reception.

A lightweight hardware-based measurement platform was also set up. This platform targets specific smartphone models, where the internal architecture allows an easy separation of the radio
frequency networking module. This platform has been used to collect energy consumption data in two scenarios: video streaming and phone calls.

Based on these experiments, we modeled the following functions:
- the random access procedure used by the user equipment to connect to the radio access network;
- the radio resource control connection procedure;
- the control traffic transmitted by the user equipment while in the connected state;
- the data traffic transmitted by the user equipment;
- the network attachment procedure used by the user equipment when connecting to the core network (e.g. at start-up, or when exiting airplane mode);
- establishment of a terminating call;
- establishment of an initiated call.

We also defined a few general scenarios of interest, as follows:
- streaming a video from a streaming platform, using a given wireless technology (3G, 4G, 5G, WiFi).
- making a phone call, using a given technology (circuit-switched, VoWiFi, VoLTE, VoNR).
- receiving a phone call, using a given technology (circuit switched, VoWiFi, VoLTE, VoNR).
- sending an SMS.
- receiving an SMS.

Regarding adaptive solutions, we mainly focused on two network scenarios, where reconfigurations are required. The first scenario consists of robotic base stations, which can move and be autonomously deployed in areas where supplementary capacity is required. A major objective in this case is to reconfigure the network and follow the traffic peaks with a reduced energy consumption. The second scenario of interest consists of sliced networks. In this case, switching off base stations is becoming more challenging, and this pushed us to design new mechanisms for energy consumption reduction.

The data collection campaign will continue, and we will produce an exhaustive set of energy consumption models.

- A.T.-J. Akem, B. Bütün, M. Gucciardo, M. Fiore, Henna:
Hierarchical Machine Learning Inference in Programmable
Switches, NativeNI 2022, Rome, Italy, Dec 2022.
- M. Gucciardo, A.T.-J. Akem, B. Bütün, M. Fiore, Demonstrating
Flow-Level In-Switch Inference, IEEE INFOCOM 2023 demo
session, New York, USA, May 2023.
- A.T.-J. Akem, B. Bütün, M. Gucciardo, M. Fiore, Showcasing
In-Switch Machine Learning Inference, NetSoft 2023 demo
session, Madrid, Spain, Jun 2023.
- B. Bütün, A.T.-J. Akem, M. Gucciardo, M. Fiore, Fast Detection of Cyberattacks on the Metaverse through User-plane Inference,
IEEE MetaCom 2023, Kyoto, Japan, Jun 2023.
- H. Pann Phyu, D. Naboulsi, R. Stanica, G. Poitau. Towards Energy Efficiency in RAN Network Slicing. IEEE LCN 2023, Daytona Beach, USA, Oct 2023.
- H. Pann Phyu, R. Stanica, D. Naboulsi, G. Poitau. Going Green in RAN Slicing. NetMob 2023, Madrid, Spain, Oct 2023.
- R. Bogdan, C. Paliuc, M. Crisan-Vida, S. Nimara and D.
Barmayoun, Low-Cost Internet-of-Things Water-Quality
Monitoring System for Rural Areas, Sensors, 23, 3919, Apr. 2023
- B. Sosdian, R. Bogdan, A. Bild, and M. Marcu Sun Tracking System For Photovoltaic Panels In The Context Of Smart Cities
Applications, 2023 IEEE International Smart Cities Conference,
ISC2 2023, Bucharest, Sep. 2023
- D. C. Apostol, P . D. Rusovan, M, Marcu, UML to code,
and code to UML, a view inside implementation challenges and
cost, 2022 26th International Conference on System Theory,
Control and Computing (ICSTCC), Sinaia, Oct. 2022
- A. G. Gherman, M. Marcu, Instrumentation and Analyzis of
Handover in Wi-Fi Networks, 2022 International Symposium on
Electronics and Telecommunications (ISETC), Timisoara, Nov.
2022
- A.T.-J .Akem, B. Bütün, M. Gucciardo, M. Fiore, Jewel:
Resource-Efficient Joint Packet and Flow Level Inference in
Programmable Switches IEEE INFOCOM 2024, Vancouver,
Canada, May 2024
- M. Gucciardo, B. Bütün, A.T.-J. Akem, M. Fiore, Evaluating the
Impact of Flow Length on the Performance of In-Switch Inference
Solutions CNERT 2024, Vancouver, Canada, May 2024
- A.T.-J. Akem, M. Gucciardo, M. Fiore, Ultra-Low Latency
User-Plane Cyberattack Detection in SDN-based Smart Grids
EnergySP 2024, Singapore, May 2024
- E. Theingi, S. Lokman, D. Naboulsi. Energy-efficient Robotic
Airborne Base Stations Deployment and Operation for
Sustainable 6G Networks. IEEE ICC Workshops 2024, Denver,
USA, June 2024
- S. Yahya, R. Stanica. Assessing the Energy Impact of Cell Switch Off at an Urban Scale, STWiMob 2024, Paris, France, October 2024

The energy consumption of mobile networks has been the source of animated debates in the recent period, with the deployment of 5G technologies. However, the energy consumption estimations put forward by the different parties in the debate showed significant differences, up to two orders of magnitude. This is a result of a lack of accurate models and meaningful metrics in this field. More precisely, the control plane of a mobile network represents a significant share of the traffic exchanged between the user and the network infrastructure, much more than in any other network technology, and this role will become even more important with the development of network function virtualisation and orchestration. Models focusing on the application-level traffic and presenting energy consumption as Joules/bit are bound to make harsh approximations and assumptions, leading to results that can not really help the involved parties, be it industrial stake-holders, policy makers or the general public.

Project ECOMOME addresses this problem of accurately modelling and optimising the energy consumption of a mobile network, with a focus on 4G and 5G technologies. This will be achieved through three main research axes. The first contribution will be represented by the first independent measurement study of energy consumption in a mobile network. We will address both user equipment and the radio access network, conducting a network metrology study on real operational networks and on experimental testbeds. The measurement data collected in this campaign will represent the input for other contributions in the project, but it will also be made openly available to the research community.

The second objective of the project is to use this measurement data in order to design accurate energy consumption models for mobile networks. In this sense, we take an original approach with respect to the literature, by focusing on modelling the impact of the building blocks of the mobile network, a series of "atomic" network mechanisms and functions which practically compose any service scenario and any user context. Modelling these atomic network mechanisms requires a detailed knowledge of the way a mobile network functions, but then allows the accurate modelling of any general scenario.

Finally, the project also targets the proposal of energy efficient networking solutions. Indeed, the measurement data and the energy consumption models will allow us to detect the most energy-hungry phases in a mobile network. To reduce their impact, we will propose network intelligence solutions, which are based on observing the traffic transported by the network, detecting whenever the network settings are over-consuming, and adapting the network configuration with energy efficiency metrics in mind.

To achieve these objectives, the ECOMOME project brings together 4 partners with a significant expertise on different topics related to mobile networks: cellular network architectures (ETS Montreal), network metrology (INSA Lyon), energy consumption (UP Timisoara) and network intelligence (IMDEA Networks Madrid).

The results of the project will have a triple utility: 1) they will provide a new modelling approach and new network intelligence solutions to the academic and industrial community working on mobile networks; 2) they will help policy makers in their decisions regarding the future evolution and deployment of mobile network technologies, and 3) they will allow the general public to easily and intuitively assess the energy consumption of their mobile equipment and of the network infrastructure in a variety of scenarios.