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The market of connected devices, IoT devices in particular, is hotter than ever. Today, lightweight IoT devices are used in several sectors, such as smart cities, smart homes, healthcare, and the manufacturing industry.IoT solutions help increase productivity by predictive maintenance and resource management in the industry. Devices with voice interfaces are spreading rapidly in the home automatio
Data-driven software is becoming prevalent, especially with the advent of machine learning and artificial intelligence. With data-driven systems come both challenges - to keep collecting and maintaining high quality data - and opportunities - open innovation by sharing data with others. We propose Open Data Collaboration (ODC) to describe pecuniary and non-pecuniary sharing of open data, similar t
5G promises to usher in the industrial 4.0 era. In that era, intricately managed autonomous industrial sites with for example remotely controller equipment and autonomous units promise previously unseen levels of efficiency. Although such scenarios are elusive, they come with strict long-since established safety requirements. To uphold such requirements, intelligent industrial 5G networks, that ac
This experience article describes lessons learned as we conducted experiments in a Kubernetes‐based environment, the most notable of which was that the performance of both the Kubernetes control plane and the deployed application depends strongly and in unexpected ways on the performance of the etcd database. The article contains (a) detailed descriptions of how networking with and without Istio w
Recent advances in autonomous vehicles present new opportunities in Intelligent transportation systems (ITS) to address urban transport challenges. Therefore, urban traffic scenarios, and in particular intersections as a bottleneck of transportation network, has received significant attention. In this paper we investigate intelligent traffic control mechanisms for autonomous vehicles at intersecti
Cloud-RAN (C-RAN) is a promising paradigm for the next generation radio access network infrastructure, which offers centralized and coordinated base-band signal processing in a BBU pool. This requires extremely low latency fronthaul links to achieve real-time signal processing. In this paper, we investigate massive MIMO pilot scheduling in a C-RAN infrastructure under a factory automation scenario
Side-channel attacks on cryptographic algorithms targets the implementation of the algorithm. Information can leak from the implementation in several different ways and, in this paper, electromagnetic radiation from an FPGA is considered. We examine to which extent key information from an AES implementation can be deduced using a low-end oscilloscope. Moreover, we examine how the antenna's distanc
Massive multiple-input multiple-out (MIMO) technology and mm wave are important technologies in 5G/6G to enhance the spectrum efficiency and system capacity. However, it has a lot of challenges in mm wave range, such as high hardware cost and power consumption in such systems. Hybrid beamforming is an interesting solution with less number of RF transvers than antennas. In this paper, we will prese
We demonstrate how to compute radome reference cases for benchmarkingradome codes. Radomes are electrically large structures, and to facilitate thecomputations a rotationally symmetric structure is assumed. We show howto implement this in the commercial software Comsol Multiphysics, and howto extract the relevant data for comparison. Two example geometries areanalyzed: a spherical shell radome, an
As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.The radio ac
The Internet of Things (IoT) paradigm, has opened up the possibility of using the ubiquity of small devices to route information without the necessity of being connected to a Wide Area Network (WAN). Use cases of IoT devices sending updates that are routed and delivered by other IoT devices have been proposed in the literature. In this paper we focus on receivers only interested in the freshest up
The implementation of circular initiatives requires certain capabilities and knowledge that traditional business models often lack, requiring new perspectives and external collaborations. This paper explores the competency needs and partnership dynamics of established companies collaborating for business model innovation for circularity through a case study of a gap exploiter business model, a com
Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Government Data (OGD), where public agencies share da
Big Data analytics and Artificial Intelligence (AI) technologies have become the focus of recent research due to the large amount of data. Dimensionality reduction techniques are recognized as an important step in these analyses. The multidimensional nature of Quality of Experience (QoE) is based on a set of Influence Factors (IFs) whose dimensionality is preferable to be higher due to better QoE
Current FPGA programming tools require extensive hardware-specific manual code tuning to achieve performance, which is intractable for most software application teams. We present HPVM2FPGA, a novel end-to-end compiler and autotuning system that can automatically tune hardware-agnostic programs for FPGAs. HPVM2FPGA uses a hardware-agnostic abstraction of parallelism as an intermediate representatio
Bayesian optimization (BO) has become an established framework and popular tool for hyperparameter optimization (HPO) of machine learning (ML) algorithms. While known for its sample-efficiency, vanilla BO can not utilize readily available prior beliefs the practitioner has on the potential location of the optimum. Thus, BO disregards a valuable source of information, reducing its appeal to ML prac
While Weighted Lasso sparse regression has appealing statistical guarantees that would entail a major real-world impact in finance, genomics, and brain imaging applications, it is typically scarcely adopted due to its complex high-dimensional space composed by thousands of hyperparameters. On the other hand, the latest progress with high-dimensional hyperparameter optimization (HD-HPO) methods for
