相关论文: ETAP: Energy-aware Timing Analysis of Intermittent…

Energy models can be constructed by characterizing the energy consumed by executing each instruction in a processor's instruction set. This can be used to determine how much energy is required to execute a sequence of assembly instructions,…

Accurately estimating workload runtime is a longstanding goal in computer systems, and plays a key role in efficient resource provisioning, latency minimization, and various other system management tasks. Runtime prediction is particularly…

Static program analysis by abstract interpretation is an efficient method to determine properties of embedded software. One example is value analysis, which determines the values stored in the processor registers. Its results are used as…

In this paper, we study cross-layer optimization of low-power wireless links for reliability-aware applications while considering both the constraints and the non-ideal characteristics of the hardware in Internet-of-things (IoT) devices.…

In industry 4.0, predictive maintenance(PM) is one of the most important applications pertaining to the Internet of Things(IoT). Machine learning is used to predict the possible failure of a machine before the actual event occurs. However,…

Energy theft, characterized by manipulating energy consumption readings to reduce payments, poses a dual threat-causing financial losses for grid operators and undermining the performance of smart grids. Effective Energy Theft Detection…

We consider an Internet-of-Things (IoT) system in which an energy harvesting powered sensor node monitors the phenomenon of interest and transmits its observations to a remote monitor over a Gaussian channel. We measure the timeliness of…

Hybrid electric vehicles (HEVs) have an over-actuated system by including two power sources, a battery pack and an internal combustion engine. This feature of HEV is exploited in this paper to simultaneously achieve accurate identification…

Simultaneous wireless information and power transfer (SWIPT) provides a promising solution for enabling perpetual wireless networks. As energy efficiency (EE) is an im- portant evaluation of system performance, this thesis studies…

IoT and edge-based inference systems require unique solutions to overcome resource limitations and unpredictable environments. In this paper, we propose an environment-aware dynamic pruning system that handles the unpredictability of edge…

In recent years, edge computing has become a popular choice for latency-sensitive applications like facial recognition and augmented reality because it is closer to the end users compared to the cloud. Although infrastructure providers are…

To build energy-efficient apps, there is a need to estimate and analyze their energy consumption in typical usage scenarios. The energy consumption of Android apps could be estimated via software-based and hardware-based approaches.…

The ensemble empirical mode decomposition (EEMD) and its complete variant (CEEMDAN) are adaptive, noise-assisted data analysis methods that improve on the ordinary empirical mode decomposition (EMD). All these methods decompose possibly…

Synchronized Random Access Channel (RACH) attempts by Internet of Things (IoT) devices could result in Radio Access Network (RAN) overload in LTE-A. 3GPP adopted Barring Bitmap Enabled-Extended Access Barring (EAB-BB) mechanism that…

In this paper, we present a model-based periodic event-triggered control mechanism for nonlinear continuous-time Networked Control Systems. A sampled-data prediction of the system behavior is used at the actuator to reduce the amount of…

The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…

Internet of Things (IoT) devices can apply mobile-edge computing (MEC) and energy harvesting (EH) to provide the satisfactory quality of experiences for computation intensive applications and prolong the battery lifetime. In this article,…

We compare the predicted phase behaviour of lead (Pb) using three different interatomic potential models, including an embedded atom method (EAM), a modified embedded atom method (MEAM), and a neural network-based machine-learned model in…

Heterogeneous systems commonly adopt dynamic scheduling algorithms to improve resource utilization and enhance scheduling flexibility. However, such flexibility may introduce timing anomalies, wherein locally reduced execution times can…

This paper presents a 3-step system that estimates the real-time energy expenditure of an individual in a non-intrusive way. First, using the user's smart-phone's sensors, we build a Decision Tree model to recognize his physical activity…