Use Cases for Energy Efficiency Management

Use Cases This section describes a number of relevant use cases with the purpose of elicit requirements for Energy Efficiency Management. This is a work in progress and additional use cases will be documented in next versions of this document. Use cases which are not tied enough to the current GREEN chater will be moved to the GREEN WG wiki pages or to other WGs or RGs.

Incremental Application of the GREEN Framework This section describes an incremental example of usage showing how a product, a service and a network can use the framework in different settings. This use case is the less trendy of all the use cases by far as its ambitious is limited to migration and coexistence, as usual. Nevertheless from a telco perspective, it is the centrality for 2 main reasons:

to start immediatly the move to energy efficiency using legacy devices;
to account the gain of the move one started;

Once upon a time there was an very old legacy router named Rusty equipped with outdated ethernet and ugly optical interfaces. Despite his worn-out appearance, Rusty was determined to contribute to the energy efficiency effort. He dreamed of finding a way to optimize his old circuits and help reduce the power consumption of the network he had faithfully served for so many years. Though he was no longer in his prime, Rusty believed that even an old router like him could make a difference in a world striving for sustainability and help reduce the carbon footprint. He is convince that he still had a part to play in making the digital world a greener place. Device moving gradually to GREEN energy efficiency support:

step 1 "baseline" : establishing a reference point of typical energy usage, which is crucial for identifying inefficiencies and measuring improvements over time. At this step the controler use only the (c) part of the framework. It is collected from the datasheet.

By establishing a baseline and using benchmarking, you can determine if your networking equipment is performing normally or if it is "off" from expected performance, guiding you in making necessary improvements. The initial measurement of your networking equipment's energy efficiency and performance, aka Baselining, needs to be in coordination with the vendor specifications and industry standards to understand what is considered normal or optimal performance. example: Baseline: Your switches operate at 5 Gbps per watt. Benchmarking: Vendor specification is 8 Gbps per watt; industry standard is 10 Gbps per watt. Action: Implement energy-saving measures and upgrades. Tracking: Measure again to see if efficiency improves towards 8-10 Gbps per watt.

step 2 "component": part of the device hw or sw migrated to support GREEN framework elements.
step 3 "device controleur"
step 4 "network level"

(i) Avoid a power-on/power-off frequency to break component parts (aka laser, power parts, wire connectors ...) (ii) the gain must be measurable (iii) network-wide energy efficiency solutions must include legacy devices and green-wg ready devices

Selective reduction of energy consumption in network parts proportional to traffic levels Traffic levels in a network follow patterns reflecting the behavior of consumers. Those patterns show periodicity in the terms of the traffic delivered, that can range from daily (from 00:00 to 23:59) to seasonal (e.g., winter to summer), showing peaks and valleys that could be exploited to reduce the consumption of energy in the network proportionally, in case the underlying network elements incorporate such capabilities. The reduction of energy consumption could be performed by leveraging on sleep modes in components up to more extreme actions such as switching off network components or modules. Such decisions are expected to no impact on the service delivered to customers, and could be accompanied by traffic relocation and / or concentration in the network.

Reporting on Lifecycle Management Lifecycle information related to manufacturing energy costs, transport, recyclability, and end-of-life disposal impacts is part of what is called "embedded carbon." This information is considered to be an estimated value, which might not be implemented today in the network devices. It might be part of the vendor information, and to be collected from datasheets or databases. In accordance with ISO 14040/44, this information should be considered as part of the sustainable strategy related to energy efficiency. Also, refer to the ecodesign framework [(EU) 2024/1781] published in June by the European Commission.

Carbon Reporting To report on carbon equivalents for global reporting, it is important to correlate the location where the specific entity/network element is operating with the corresponding carbon factor. Refer to the world emission factor from the International Energy Agency (IEA), electricity maps applications that reflect the carbon intensity of the electricity consumed, etc.

Energy Mix Energy efficiency is not limited to reducing the energy consumption, it is common to include carbon free, solar energy, wind energy, cogeneration in the efficiency. The type of the sources of energy of the power is one criteria of efficiency. There are other dimensions that must visible: As many telecom locations include battery or additionnally several backups levels (as example battery, standby generator ...) there is a requirement to known exactly when a backup power is in used and which one is.

Real-time Energy Metering of Virtualised or Cloud-native Network Functions Facilitating more precise and real-time estimations of energy consumed by virtualised or cloud-native network functions. Effective metering of virtualized network infrastructure is critical for the efficient management and operation of next-generation mobile networks .

Indirect Energy Monitoring and control There are cases where Energy Management for some devices need to report on other entities. There are two major reasons for this. o For monitoring energy consumption of a particular entity, it is not always sufficient to communicate only with that entity. When the entity has no instrumentation for determining power, it might still be possible to obtain power values for the entity via communication with other entities in its power distribution tree. A simple example of this would be the retrieval of power values from a power meter at the power line into the entity. A Power Distribution Unit (PDU) and a Power over Ethernet (PoE) switch are common examples. Both supply power to other entities at sockets or ports, respectively, and are often instrumented to measure power per socket or port. Also it could be considered to obtain power values for the entity via communication with other entities outside of the power distribution tree, like for example external databases or even data sheets. o Similar considerations apply to controlling the power supply of an entity that often needs direct or indirect communications with another entity upstream in the power distribution tree. Again, a PDU and a PoE switch are common examples, if they have the capability to switch power on or off at their sockets or ports, respectively.

Consideration of other domains for obtention of end-to-end metrics The technologies under the scope of IETF provide the necessary connectivity to other technological domains. For the obtention of metrics end-to-end it would be required to combine or compose the metrics per each of those domains. An exemplary case is the one of a network slice service. The concept of network slice was initially defined by 3GPP , and it has been further extended to the concerns of IETF . In regards energy efficiency, 3GPP defines a number of energy-related key performance indicators (KPI) in , specifically Energy Efficiency (EE) and Energy Consumption (EC) KPIs. There are KPIs particular for a slice supporting a specific kind of service (e.g., Mobile Broadband or MBB), or generic ones, like Generic Network Slice EE or Network Slice EC. Assuming these as the KPIs of interest, the motivation of this use case is the obtention of the equivalent KPIs at IETF level, that is, for the network slice service as defined in . Note that according to , the Generic Network Slice EE is the performance of the network slice divided by the Network Slice EC. Same approach can be followed at IETF level. Note that for avoiding double counting the energy at IETF level in the calculation of the end-to-end metric, the 3GPP metric should only consider the efficiency and consumption of the 3GPP-related technologies.

Dynamic adjustment of network element throughput according to traffic levels in wireless transport networks Radio base stations are typically connected to the backbone network by means of fiber or wireless transport (e.g., microwave) technologies. In the specific case of wireless transport, automation frameworks have been defined for their control and management. One of the parameters subject of automated control is the power of the radio links. The relevance of that capability is that the power can be adjusted accordingly to the traffic observed. Wireless transport networks are typically planned to support the maximum traffic capacity in their area of aggregation, that is, the traffic peak. With that input, the number of radio links in the network element and the corresponding power per radio link (for supporting a given modulation and link length in the worst weather conditions) are configured. This is done to avoid any kind of traffic loss in the worst operational situation. However, such operational needs are sporadic, giving room for optimization during normal operational circumstances and/or low traffic periods. Power-related parameters are for instance defined in . Those power parameters can be dynamically configured to adjust the power to the observed traffic levels with some coarse granularity, but pursuing certain degrees of proportionality.

Video streaming use case Video streaming is nowadays the major source of traffic observed in ISP networks, in a propotion of 70% or even higher. Over-the-top distribution of streaming traffic is typically done by delivering a unicast flow per end user for the content of its interest.In consequence, during the hours of higher demand, the total traffic in the network is proportional to the concurrence of users consuming the video streaming service. The amount of traffic is also dependent of the resolution of the encoded video (the higher the resolution, the higher the bit rate per video flow), which tends to be higher as long as the users devices support such higher resolutions. The consequence of both the growth in the number of flows to be supported simultaneously, and the higher bit rate per flow, is that the nework elements in the path between the source of the video and the user have to be dimensioned accordingly. This implies the continuous upgrade of those network elements in terms of capacity, with the need of deploying high-capacity network elements and components. Apart from the fact that this process is shortening the lifetime of network elements, the need of high capacity interfaces also increase the energy consumption (despite the effort of manufacturers in creating more efficient network element platforms). Note that nowadays there is no actual possibility of activating energy consumption proportionality (in regards the delivered traffic) to such network elements. As a mean of slowing down this cycle of continuos renewal, and reduce the need og higher bit rate interfaces / line cards, it seems convenient to explore mechanisms that could reduce the volume of traffic without impacting the user service expectations. Variants of multicast or different service delivery strategies can help to improve the energy efficiency associated to the video streaming service. It should be noted that another front for optimization is the one related to the deployment of cache servers in the network.

WLAN Network Energy Saving In a WLAN network, The AP is usually powered by a PoE switch. AP nodes are network devices with the largest number and consuming most of energy. Therefore, the working status of the AP is the core of the energy saving solution. The working status of the AP can be break down into 3 modes as follows: PoE power-off mode: In this mode, the PoE switch shuts down the port and stops supplying power to the AP. The AP does not consume power at all. When the AP wakes up, the port provides power again. In this mode, it usually takes a few minutes for the AP to recover. Hibernation mode: Only low power consumption is used to protect key hardware such as the CPU, and other components are shut down. Low power consumption mode: Compared with the hibernation mode, the low power consumption mode maintains a certain communication capability. For example, the AP retains only the 2.4 GHz band and disables other radio bands. In energy saving deployment, after the surrounding energy saving APs are shut down, the Working AP automatically adjusts their transmit power to increase the coverage of the entire area at specific energy saving period. In such case, energy saving APs can freely choose to switch to any mode we described above.

PoE Power Off Mode

Low Power Consumption Mode

Wireless Resource Management on APs

Fixed Network Energy Saving Traffic on the Tidal network has an obvious tidal period, including heavy-traffic periods and light-traffic periods: The time duration of heavy traffic load and light traffic load are clearly distinguished. The switching time between the heavy-traffic period and the light-traffic period is quite fixed and cyclic. In a tidal network, some network devices can be shut down or sleep during low-traffic periods to save energy. In the metro or backbone network, the routers support various different speed interfaces, e.g., the gigabit level to 10GE/50GE, or 100G to 400G. Routers might choose to adjust speed of the interface or downgrade from high speed interface to low speed interface based on network traffic load changes to save the energy. In addition, the routers can adjust the number of working network processor cores and clock frequency of chipsets and the number of SerDes buses based on network traffic load changes to save the energy.

Energy Efficiency Network Management Network level Energy Efficiency allows network operators not only see real time energy consumption in the network devices of large scale network, but also allow you see o which network devices enable energy saving, which devices not,which are legacy ones, o The total energy consumption changing trend over the time of the day, for all network devices, o Energy efficiency changing trend over the time of the day for the whole network. With the better observability to energy consumption statistics data and energy efficiency statistics data, the network operators can know which part of the network need to be adjusted or optimized based on network status change.

ISAC-enabled Energy-Aware Smart City Traffic Management

Use case description Integrated Sensing and Communications (ISAC) is emerging as a key enabler for next-generation wireless networks, integrating sensing and communication functionalities within a unified system. By leveraging the same spectral, hardware, and computational resources, ISAC enhances network efficiency while enabling new capabilities such as high-resolution environment perception, object detection, and situational awareness. This paradigm shift is particularly relevant for applications requiring both reliable connectivity and precise sensing, such as autonomous vehicles, industrial automation, and smart city deployments. Given its strategic importance, ISAC has gained significant traction in standardization efforts. The ETSI Industry Specification Group (ISG) on ISAC has been established to explore technical requirements and use cases, while 3GPP has initiated discussions on ISAC-related features within its ongoing research on future 6G systems. Furthermore, research initiatives within the IEEE and IETF are investigating how ISAC can be integrated into network architectures, spectrum management, and protocol design, making it a critical area of development in the evolution of wireless networks. This use case involves deploying ISAC systems in a smart city to monitor and optimize vehicles' traffic flows while minimizing energy consumption of the mobile network. The system integrates sensing technologies, such as radar and LIDAR, with communication networks to detect vehicle density, monitor road conditions, and communicate with autonomous vehicles or traffic lights. By using ISAC, the system minimizes redundant infrastructure (e.g., separate sensors and communication equipment), thus reducing the overall carbon and energy footprint.

GREEN Specifics Energy Consumption Monitoring: Each ISAC component (e.g., roadside units, integrated sensors, and communication transceivers) is capable of reporting its energy consumption in real time to the centralized or distributed energy management system. Reconfiguration for Energy Efficiency: The system can dynamically switch between high-resolution sensing modes (e.g., during peak hours) and low-power modes (e.g., during low traffic periods). The network can reconfigure traffic communication paths to prioritize routes or nodes that consume less power, leveraging energy-efficient communication protocols. Integration of Local and Global Energy Goals: The system can operate both locally (e.g., turning off specific roadside units in low- traffic areas) and globally (e.g., modifying traffic patterns across the city) to achieve defined energy consumption goals.

Requirements for GREEN

Measurement Granularity:

Ability to measure energy consumption per ISAC component (e.g., roadside unit, sensor, transceiver).
Granular reporting per communication link or sensing mode (e.g., high-power radar mode vs. low-power mode).

Power Control Mechanisms:

Ability to switch components on/off or place them in sleep/standby mode when not in use.
Support for dynamic adjustment of sensing resolution or communication bandwidth to balance energy savings and system performance.

Reconfiguration and Adaptability:

Support for hardware reconfiguration (e.g., adaptive sensing modes, transceiver settings) to optimize energy use.
Mechanisms to steer traffic or adjust network routing based on global or local energy-saving objectives.

Global Coordination:

Capabilities for cross-domain coordination to enable global optimization (e.g., city-wide traffic rerouting or dynamic resource allocation across different regions).
Ability to aggregate and analyze energy consumption data from all ISAC components to inform high-level decision-making.

Energy-Aware Standards and Protocols:
- Communication protocols that minimize power usage while maintaining reliability.
- Interoperability standards for energy-aware reconfiguration across heterogeneous ISAC components and systems.

Double Accounting Open issue Energy consumption monitoring often includes metering at both upstream and downstream levels of power distribution. While this can provide granular visibility, it may also lead to double accounting if not carefully managed. A common case arises when energy is measured at the input of a Power Delivery Unit (PDU), and individually at each device powered by that PDU (e.g., servers, switches). Since the PDU input already reflects the downstream consumption, summing the per-device values with the PDU input results in redundant reporting. A similar issue occurs with Power over Ethernet (PoE) infrastructures when a network switch supply power directly to devices. If the total power consumption measured encompasses both the power delivered to the PoE switch and to the powered devices, this again results in double accounting. These 2 cases distort energy dashboards and indicators such as Power Usage Effectiveness (PUE).