Related papers: DIAC: Design Exploration of Intermittent-Aware Com…
User experience on mobile devices is constrained by limited battery capacity and processing power, but 6G technology advancements are diving rapidly into mobile technical evolution. Mobile edge computing (MEC) offers a solution, offloading…
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this…
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud,…
This paper studies Integrated Sensing, Communication, and Powering (ISCAP) as a novel framework designed to enhance Internet of Things (IoT) applications within sixth-generation wireless networks. In these applications, in addition to IoT…
Energy harvesting offers an attractive and promising mechanism to power low-energy devices. However, it alone is insufficient to enable an energy-neutral operation, which can eliminate tedious battery charging and replacement requirements.…
We propose Zygarde -- which is an energy -- and accuracy-aware soft real-time task scheduling framework for batteryless systems that flexibly execute deep learning tasks1 that are suitable for running on microcontrollers. The sporadic…
Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we…
With the increasing number of Internet of Things (IoT) devices, Machine Type Communication (MTC) has become an important use case of the Fifth Generation (5G) communication systems. Since MTC devices are mostly disconnected from Base…
In the era of the sixth generation (6G) and industrial Internet of Things (IIoT), an industrial cyber-physical system (ICPS) drives the proliferation of sensor devices and computing-intensive tasks. To address the limited resources of IIoT…
Integrated sensing and communication (ISAC) boosts network efficiency by using existing resources for diverse sensing applications. In this work, we propose a cell-free massive MIMO (multiple-input multiple-output)-ISAC framework to detect…
Despite the increasing development of Artificial Intelligence (AI) systems, Requirements Engineering (RE) activities face challenges in this new data-intensive paradigm. We identified a lack of support for problem discovery within AI…
In-Memory Computing (IMC) has emerged as a promising paradigm for energy-efficient, throughput-efficient and area-efficient machine learning at the edge. However, the differences in hardware architectures, array dimensions, and fabrication…
Dalek is an experimental compute cluster designed to evaluate the performance of heterogeneous, consumer-grade hardware for software design, prototyping, and algorithm development. In contrast to traditional computing centers that rely on…
Integrated sensing and communication (ISAC) is an emerging technology in next-generation communication networks. However, the communication performance of the ISAC system may be severely affected by interference from the radar system if the…
This paper explores the energy efficiency (EE) of integrated sensing and communication (ISAC) systems employing massive multiple-input multiple-output (mMIMO) techniques to leverage spatial beamforming gains for both communication and…
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by…
In real-time Industrial Internet of Things (IIoT), e.g., monitoring and control scenarios, the freshness of data is crucial to maintain the system functionality and stability. In this paper, we propose an AoI-Aware Deep Learning (AA-DL)…
Efficiently estimating system dynamics from data is essential for minimizing data collection costs and improving model performance. This work addresses the challenge of designing future control inputs to maximize information gain, thereby…
To enhance the performance of aerial-ground networks, this paper proposes an integrated sensing and communication (ISAC) framework for multi-UAV systems. In our model, ground base stations (BSs) cooperatively serve multiple unmanned aerial…
Data collected and transmitted by Internet of things (IoT) devices are typically used for control and monitoring purposes; and hence, their timely delivery is of utmost importance for the underlying applications. However, IoT devices…