Related papers: ETAP: Energy-aware Timing Analysis of Intermittent…
Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy…
The use of machine learning for time series prediction has become increasingly popular across various industries thanks to the availability of time series data and advancements in machine learning algorithms. However, traditional methods…
Energy modeling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processors exist, most do not account for processor-specific…
This paper develops a novel approach to obtaining energy-efficient transmission schedules for delay-limited bursty data arrivals under non-ideal circuit power consumption. Assuming a-prior knowledge of packet arrivals, deadlines and channel…
Energy modelling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processors exist, most do not account for processor-specific…
Estimating the dissipation, or the entropy production rate (EPR), can provide insights into the underlying mechanisms of nonequilibrium driven processes. Experimentally, however, only partial information can be accessed, and the ability to…
Catheter ablation has limited therapeutic efficacy against non-paroxysmal atrial fibrillation (AF), and electrophysiological studies using mapping catheters have been applied to evaluate the AF substrate. However, many of these approaches…
Advancement of chip technology will make future computer chips faster. Power consumption of such chips shall also decrease. But this speed gain shall not come free of cost, there is going to be a trade-off between speed and efficiency, i.e…
A smart home energy dataset that records miscellaneous energy consumption data is publicly offered. The proposed energy activity dataset (EAD) has a high data type diversity in contrast to existing load monitoring datasets. In EAD, a simple…
We consider wireless-powered amplify-and-forward and decode-and-forward relaying in cooperative communications, where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source and…
Multi-access Edge Computing (MEC) delivers low-latency services by hosting applications near end-users. To promote sustainability, these systems are increasingly integrated with renewable Energy Harvesting (EH) technologies, enabling…
This paper presents CARTOS, a charging-aware real-time operating system designed to enhance the functionality of intermittently-powered batteryless devices (IPDs) for various Internet of Things (IoT) applications. While IPDs offer…
We consider joint energy storage management and load scheduling at a residential site with integrated renewable generation. Assuming unknown arbitrary dynamics of renewable source, loads, and electricity price, we aim at optimizing the load…
This paper introduces Energentic Intelligence, a class of autonomous systems defined not by task performance, but by their capacity to sustain themselves through internal energy regulation. Departing from conventional reward-driven…
Recent advancements in IoT technologies have underscored the importance of using sensor data to understand environmental contexts effectively. This paper introduces a novel embedded system designed to autonomously label sensor data directly…
Intermittently powered devices enable new applications in harsh or inaccessible environments, such as space or in-body implants, but also introduce problems in programmability and correctness. Researchers have developed programming models…
In this paper, we study the peak-aware energy scheduling problem using the competitive framework with machine learning prediction. With the uncertainty of energy demand as the fundamental challenge, the goal is to schedule the energy output…
In this paper, we address the power-aware scheduling of sporadic constrained-deadline hard real-time tasks using dynamic voltage scaling upon multiprocessor platforms. We propose two distinct algorithms. Our first algorithm is an off-line…
Wireless power transfer (WPT) using energy beamforming is a promising solution for low power Internet of Things (IoT) devices. In this work, we consider WPT from an energy transmitter (ET) employing retrodirective WPT using a large phased…
Energy harvesting (EH) provides a means of greatly enhancing the lifetime of wireless sensor nodes. However, the randomness inherent in the EH process may cause significant delay for performing sensing operation and transmitting the sensed…