A method of for performing carbon neutralization in a communication network is provided. The method includes receiving a service task from a user equipment. The method also includes obtaining a carbon neutralization calculation parameter related to performing the received service task. The method further includes selecting, based on the obtained carbon neutralization calculation parameter, a target entity from a plurality of candidate targets at which the received service task can be performed. The method further includes sending the received service task to the selected target entity.

Methods, systems, and apparatus for monitoring and controlling electronic devices using wired and wireless protocols are disclosed. The systems and apparatus may monitor their environment for signals from electronic devices. The systems and apparatus may take and disambiguate the signals that are received from the devices in their environment to identify the devices and associate control signals with the devices. The systems and apparatus may use communication means to send control signals to the identified electronic devices. Multiple apparatuses or systems may be connected together into networks, including mesh networks, to make for a more robust architecture.

Methods, systems, and apparatus for monitoring and controlling electronic devices using wired and wireless protocols are disclosed. The systems and apparatus may monitor their environment for signals from electronic devices. The systems and apparatus may take and disambiguate the signals that are received from the devices in their environment to identify the devices and associate control signals with the devices. The systems and apparatus may use communication means to send control signals to the identified electronic devices. Multiple apparatuses or systems may be connected together into networks, including mesh networks, to make for a more robust architecture.

An AI-based platform for enabling intelligent orchestration and management of power and energy is disclosed. The AI-based platform includes a set of modular, distributed energy systems that are configurable based on local demand requirements. In some embodiments, the local demand requirements are forecast by demand forecasting algorithm operating on a set of edge networking devices that are linked to a set of systems that consume energy. In some embodiments, at least one of the energy systems is configured by the AI-based platform to be located in proximity to a location and time of demand and/or to be located in proximity to a location and time of demand. In some embodiments, at least one of the energy systems is configured by the AI-based platform to generate energy at a point of local demand and/or to deliver a modular generation system to a location of demand.

An optimization apparatus that receives data related to operational characteristics of a plurality of devices in a network, classifies the plurality of devices in the network into a plurality of clusters based on the data, builds a plurality of artificial intelligence (AI) models, each of the AI models corresponding to one of the plurality of clusters, determines a predicted operational characteristic for a first device based on an AI model, among the AI models, corresponding to a cluster to which the first device belongs, and outputs a recommendation for the first device based on the predicted operational characteristics.

Technologies for performance monitoring include a computing device having multiple processor cores. The computing device performs a training workload with a processor core by continuously polling an empty input queue. The computing device determines empty polling thresholds based on the empty polling workload. The computing device performs a packet processing workload with one or more processor cores by continuously polling input queues associated with network traffic. The computing device compares a measured number of empty polls performed by the packet processing workload against the empty polling thresholds. The computing device configures power management of one or more processor cores in response to the comparison. The computing device may determine empty polling trends and compare the measured number of empty polls and the empty polling trends to the empty polling thresholds. Other embodiments are described and claimed.

Technologies for performance monitoring include a computing device having multiple processor cores. The computing device performs a training workload with a processor core by continuously polling an empty input queue. The computing device determines empty polling thresholds based on the empty polling workload. The computing device performs a packet processing workload with one or more processor cores by continuously polling input queues associated with network traffic. The computing device compares a measured number of empty polls performed by the packet processing workload against the empty polling thresholds. The computing device configures power management of one or more processor cores in response to the comparison. The computing device may determine empty polling trends and compare the measured number of empty polls and the empty polling trends to the empty polling thresholds. Other embodiments are described and claimed.

Techniques are provided for improving the environmental sustainability of a networking device and/or a networking system. In one example, a sustainability server obtains power consumption data of a networking device on a per-plane basis. Based on the power consumption data, the sustainability server computes an individual sustainability score that indicates a level of environmental sustainability of the networking device. The sustainability server further analyzes the power consumption data on the per-plane basis. In response to analyzing the power consumption data on the per-plane basis, the sustainability server provides a recommendation to implement a change to a configuration or operating parameter of the networking device, or to a networking system that includes the networking device, to improve the individual sustainability score.

Techniques are provided for improving the environmental sustainability of a networking device and/or a networking system. In one example, a sustainability server obtains power consumption data of a networking device on a per-plane basis. Based on the power consumption data, the sustainability server computes an individual sustainability score that indicates a level of environmental sustainability of the networking device. The sustainability server further analyzes the power consumption data on the per-plane basis. In response to analyzing the power consumption data on the per-plane basis, the sustainability server provides a recommendation to implement a change to a configuration or operating parameter of the networking device, or to a networking system that includes the networking device, to improve the individual sustainability score.

The present disclosure provides techniques for optimizing power consumption of Massive-Internet of Things (IoT) devices comprising a plurality of IoT devices. According to some examples, a power optimizer system may obtain one or more operational parameters of a plurality of IoT devices. The power optimizer system may estimate a Power Cost Function (PCF) based on one or more operational parameters to determine power consumption of each IoT device. The power optimizer system may determine a variation in the PCF of one or more IoT devices out of the plurality of IoT devices due to variations in uplink and downlink operations of each IoT device. The power optimizer system may identify one or more optimal operational parameters and then, configure the one or more IoT devices of the plurality of IoT devices with the one or more optimal operational parameters.