Related papers: A Chronological Analysis of the Evolution of Smart…
Information and Communication Technology (ICT) infrastructures play a key role in the evolution from traditional power systems to Smart Grids. Increasingly fluctuating power flows, sparked by the transition towards sustainable energy…
New network architectures, such as the Internet of Things (IoT), 5G, and next-generation (NextG) cellular systems, put forward emerging challenges to the design of future wireless networks toward ultra-high data rate, massive data…
Time-sensitive networking (TSN) is expected to be a key component of critical machine-type communication networks in areas such as Industry 4.0, robotics and autonomous vehicles. With rising mobility requirements in industrial applications…
In the last 15 years, the Internet architecture has continued evolving organically, introducing new headers and protocols to the classic TCP/IP stack. More specifically, we have identified two major trends. First, it is common that most…
Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no…
Neural networks have become the standard model for various computer vision tasks in automated driving including semantic segmentation, moving object detection, depth estimation, visual odometry, etc. The main flavors of neural networks…
Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly…
Information-Centric Networking (ICN), with its data-oriented operation and generally more powerful forwarding layer, provides an attractive platform for distributed computing. This paper provides a systematic overview and categorization of…
Graph is a well known data structure to represent the associated relationships in a variety of applications, e.g., data science and machine learning. Despite a wealth of existing efforts on developing graph processing systems for improving…
The emergence of Multi-Access Edge Computing (MEC) technology aims at extending cloud computing capabilities to the edge of the wireless access networks. MEC provides real-time, high-bandwidth, low-latency access to radio network resources,…
As semiconductor power density is no longer constant with the technology process scaling down, modern CPUs are integrating capable data accelerators on chip, aiming to improve performance and efficiency for a wide range of applications and…
Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in learning and predicting on large-scale data present in social networks, biology, etc. Since integrated circuits (ICs) can naturally be represented as…
Deep Neural Networks (DNNs) have become ubiquitous in medical image processing and analysis. Among them, U-Nets are very popular in various image segmentation tasks. Yet, little is known about how information flows through these networks…
Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at…
The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things…
The Internet of Things (IoT) has revolutionized the way devices communicate and interact with each other, but it has also created new challenges in terms of security. In this context, intrusion detection has become a crucial mechanism to…
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to…
Developing intelligent systems requires combining results from both industry and academia. In this report you find an overview of relevant research fields and industrially applicable technologies for building very large scale cyber physical…
Brain-Computer Interface (BCI) technology facilitates direct communication between the human brain and external devices, representing a substantial advancement in human-machine interaction. This review provides an in-depth analysis of…
In the creation of a smart future information society, Internet of Things (IoT) and Content Centric Networking (CCN) break two key barriers for both the front-end sensing and back-end networking. However, we still observe the missing piece…