相关论文: XGBoost energy consumption prediction based on mul…

The energy consumption of computer and communication systems does not scale linearly with the workload. A system uses a significant amount of energy even when idle or lightly loaded. A widely reported solution to resource management in…

With rapid advancements in the Internet of Things (IoT) paradigm, electrical devices in the near future is expected to have IoT capabilities. This enables fine-grained tracking of individual energy consumption data of such devices, offering…

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption.…

The expansion of residential demand response programs and increased deployment of controllable loads will require accurate appliance-level load modeling and forecasting. This paper proposes a conditional hidden semi-Markov model to describe…

Web browsing is an activity that billions of mobile users perform on a daily basis. Battery life is a primary concern to many mobile users who often find their phone has died at most inconvenient times. The heterogeneous multi-core…

Energy load forecasting plays a crucial role in optimizing resource allocation and managing energy consumption in buildings and cities. In this paper, we propose a novel approach that leverages language models for energy load forecasting.…

As power management has become a primary concern in modern data centers, computing resources are being scaled dynamically to minimize energy consumption. We initiate the study of a variant of the classic online speed scaling problem, in…

Accurate demand forecasting is critical for brick-and-mortar retailers to optimize inventory management and minimize costs. This study evaluates statistical baselines, tree-based ensembles (XGBoost and LightGBM), and deep learning…

Accurate energy consumption prediction is crucial for optimizing the operation of electric commercial heavy-duty vehicles, e.g., route planning for charging. Moreover, understanding why certain predictions are cast is paramount for such a…

The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal…

Mobile phones and other electronic gadgets or devices have aided in collecting data without the need for data entry. This paper will specifically focus on Mobile health data. Mobile health data use mobile devices to gather clinical health…

The amount of energy consumed during the execution of software, and the ability to predict future consumption, is an important factor in the design of embedded electronic systems. In this technical report I examine factors in the execution…

In this report we present a network-level multi-core energy model and a software development process workflow that allows software developers to estimate the energy consumption of multi-core embedded programs. This work focuses on a high…

This paper investigates a method to improve buildings' thermal predictive control performance via online identification and excitation (active learning process) that minimally disrupts normal operations. In previous studies we have…

Thermal management in the hyper-scale cloud data centers is a critical problem. Increased host temperature creates hotspots which significantly increases cooling cost and affects reliability. Accurate prediction of host temperature is…

The growing demand for Internet of Things (IoT) networks has sparked interest in sustainable, zero-energy designs through Energy Harvesting (EH) to extend the lifespans of IoT sensors. Visible Light Communication (VLC) is particularly…

The increased digitalisation and monitoring of the energy system opens up numerous opportunities to decarbonise the energy system. Applications on low voltage, local networks, such as community energy markets and smart storage will…

The evolving energy landscape has propelled energy communities to the forefront of modern energy management. However, existing research has yet to explore the potential synergies between data centres and energy communities, necessitating an…

Extending our prior work, we propose a multi-energy X-ray measurement model incorporating material variability with energy correlations to enable the analysis and exploration of the performance of X-ray imaging and sensing systems. Based on…

The Internet of Things (IoT) networks are expected to involve myriad of devices, ranging from simple sensors to powerful single board computers and smart phones. The great advancement in computational power of embedded technologies have…