Proprietary Hardware Research Articles

A comprehensive framework for 5G indoor localization

Localization inside legacy private 5G networks is a daunting task that involves solving the problem of indoor localization using commercial off-the-shelf proprietary hardware. While some previous work has focused on experimental analysis, none has undertaken to develop a realistic solution based on commercial equipment. In this study, we present the first comprehensive and concrete 5G framework that combines fingerprinting with the 3GPP Enhanced Cell ID (E-CID) approach. Our methodology consists of a machine-learning model to deduce the user’s position by comparing the signal strength received from the User Equipment (UE) with a reference radio power map. To achieve this, the 3GPP protocols and functions are improved to provide open, centralized, and universal localization functions. A new reference map paradigm named Optical Radio Power Estimation using Light Analysis (ORPELA) is introduced. Real-world experiments prove that it is reproducible and more accurate than state-of-the-art radio-planning software. Machine-learning models are then designed, trained, and optimized for an ultra-challenging radio context. Finally, a large-scale experimental campaign encompassing a wide range of cases, including line-of-sight or mobility, is being conducted to demonstrate expected location performance within realistic 5G private networks.

Comprehensive analysis of smart grids functionalities virtualization

The implementation of advanced digital technologies in the conventional electric grid has triggered a transformation towards an intelligent network, known as Smart Grid. The associated benefits are diverse, ranging from more efficient energy management and demand response to the distributed integration of renewable energy sources. Ultimately, this transition promotes a more reliable, sustainable, and cost-effective energy supply. In this context, there is increasing recognition of the advantages of employing intelligent at edge to provide redundancy, virtualize functions that were previously in different proprietary hardware in the same device, or introduce new functionalities into the electric grid. This study focuses on conducting a comprehensive analysis on the key aspects to consider when implementing virtualized solutions in substations. Strategies have been sought to ensure the optimal deployment of virtualized nodes within the electrical sector, taking into account factors such as functional requirements, facility types, virtualization methodologies, and node specifications, among others. Furthermore, throughout the study, several virtualization tools have been analysed to determine their feasibility and the advantages they offer when integrated into the Smart Grid.

Post-fault restoration of service function chains in fog networks

The network function virtualization (NFV) paradigm is rapidly being adopted by enterprises and service providers as an alternative to proprietary hardware. It enables virtual network functions (VNFs) to be embedded on commercial edge servers for the delivery of highly-specialized service function chains (SFCs). Here embedding SFC requests on fog computing supports clients with stringent delay requirements and contextual service requirements. Now one of the major challenges is the survivability of embedded service chains in fog computing, which may be compromised due to node, link, and application failures. These failures can disrupt service continuity and degrade the quality-of-service. Therefore, there is a demand for SFC provisioning to be more resilient, incorporating rapid restoration techniques that oppose proactive solutions that reserve backup paths, subsequently compromising network capacity. Hence, this paper presents heuristic methods for post-fault SFC restorations due to multiple failures in fog computing. These methods establish post-provisioning restoration for failed requests, known as end-to-end (E2E) and intermediate (IM) restoration, that aim to restore paths with the least delay and cost.

Detection and Determination of User Position Using Radio Tomography with Optimal Energy Consumption of Measuring Devices in Smart Buildings

The main objective of the research presented in the following work was the adaptation of reflection-radar technology in a detection and navigation system using radio-tomographic imaging techniques. As key aspects of this work, the energy optimization of high-frequency transmitters can be considered for use inside buildings while maintaining user safety. The resulting building monitoring and control system using a network of intelligent sensors supported by artificial intelligence algorithms, such as logistic regression or neural networks, should be considered an outcome. This paper discusses the methodology for extracting information from signal echoes and how they were transported and aggregated. The data extracted in this way were used to support user navigation through a building, optimize energy based on presence information, and increase the facility’s overall security level. A band from 5 GHz to 6 GHz was chosen as the carrier frequency of the signals, representing a compromise between energy expenditure, range, and the properties of wave behavior in contact with different types of matter. The system includes proprietary hardware solutions that allow parameters to be adjusted over the entire range and guarantee adaptation for RTI (radio tomography imaging) technology.

An open-source framework for the development, deployment and testing of wind farm control strategies

Recent advances in wind farm control, particularly in wake steering strategies, have attracted significant interest from both academia and industry. Wake steering consists in misaligning an upstream turbine to redirect its wake, mitigating its impact on downstream turbines. Implementing these strategies on real-time systems presents challenges, especially in collaborative research projects, for example because of the handling of confidential operational data and the complexity of deploying source code on proprietary hardware. This paper introduces a MATLAB-based framework designed to facilitate the development, deployment, and testing of wake steering strategies on real-time Bachmann PLC systems. The modular architecture of the framework is designed to address common challenges in research projects, such as model deployment, data confidentiality, adaptability to runtime changes, and more in general for the facilitation of multi-partner collaborations. The framework was used to perform multiple wake steering experiments on two 3.5 MW turbines.

FARESHARE: An open-source apparatus for assessing drinking microstructure in socially housed rats

Social factors have been shown to play a significant and lasting role in alcohol consumption. Studying the role of social context on alcohol drinking is important to understand the factors that contribute to the initiation or maintenance of casual and problematic alcohol use, as well as those that may be protective. A substantial body of preclinical research has shown that social environment such as housing conditions and social rank plays an important role in alcohol consumption and preference, though the extent of these effects have been obfuscated by methodological differences and technical challenges. Robust individual differences in alcohol intake in socially housed animals are difficult to track when animals share a common fluid source. Commercial solutions are prohibitively expensive and are limited by proprietary software and hardware (including caging systems). Here we describe FARESHARE, an affordable, open-source solution for tracking fluid consumption in socially housed rats. The device uses RFID and custom hardware to individually measure and record each rat’s fluid consumption and licking microstructure. Each bout is also timestamped such that the circadian effects of drinking behaviour may be analysed. We provide a validation showing the operation of the device in a two-bottle-choice alcohol-drinking paradigm over a nine-day period in four group-housed female rats. We show that FARESHARE is able to capture traditional measures such as daily intake and preference, as well as circadian effects, microstructure, and individual variations in drinking.

Open continuum robotics-one actuation module to create them all.

Experiments on physical continuum robot are the gold standard for evaluations. Currently, as no commercial continuum robot platform is available, a large variety of early-stage prototypes exists. These prototypes are developed by individual research groups and are often used for a single publication. Thus, a significant amount of time is devoted to creating proprietary hardware and software hindering the development of a common platform, and shifting away scarce time and efforts from the main research challenges. We address this problem by proposing an open-source actuation module, which can be used to build different types of continuum robots. It consists of a high-torque brushless electric motor, a high resolution optical encoder, and a low-gear-ratio transmission. For this article, we create three different types of continuum robots. In addition, we illustrate, for the first time, that continuum robots built with our actuation module can proprioceptively detect external forces. Consequently, our approach opens untapped and under-investigated research directions related to the dynamics and advanced control of continuum robots, where sensing the generalized flow and effort is mandatory. Besides that, we democratize continuum robots research by providing open-source software and hardware with our initiative called the Open Continuum Robotics Project, to increase the accessibility and reproducibility of advanced methods.

Modular Open-Source Design of Pyrolysis Reactor Monitoring and Control Electronics

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis plants are expensive custom designed systems. The plug-and-play prototype approach was first tested by connecting it to the pyrolysis reactor and ensuring that it can measure temperature and actuate heaters and a stirring motor. Next, a single circuit board system was created and tested using the designs from the BREAD prototype to reduce the number of microcontrollers required. Both open-source control systems were capable of reliably running the pyrolysis reactor continuously, achieving equivalent performance to a state-of-the-art commercial controller with a ten-fold reduction in the overall cost of control. Open-source, plug-and-play hardware provides a reliable avenue for researchers to quickly develop data acquisition and control electronics for industrial-scale experiments.

Development of an Arduino-based, open-control interface for hardware in the loop applications

This article presents a flexible control interface based on low-cost hardware solutions for electric drives which classically come either with a proprietary hardware solution or a high-cost interface solution. The interface presented can be used to connect a standard PC with an electric drive to enable testing simulation and control applications. The control interface is developed based on the open-source Python scripting language and Arduino’s open-source and accessible hardware. The new interface communicates with the test stand through its I/O terminals via developed electronic amplifiers and creates a solid base for further development towards more extensive hardware in the loop simulations.

Vision-based robotics using open FPGAs

Robotics increasingly provides practical applications for society, such as manufacturing, autonomous driving, robot vacuum cleaners, robots in logistics, drones for inspection, etc. Typical requirements in this field are fast response time, low power consumption, parallelism, and flexibility. According to these features, FPGAs are a suitable computing substrate for robots. A few vendors have dominated the FPGA market with their proprietary tools and hardware devices, resulting in fragmented ecosystems with few standards and little interoperation. New and complete open toolchains for FPGAs are emerging from the open-source community. This article presents an open-source library of Verilog modules useful for vision-based robots, including reusable image processing blocks for perception and reactive control blocks. This library has been developed using open tools, but its Verilog modules are fully compatible with any proprietary toolchain. In addition, three applications with a real robot and open FPGAs have been developed for experimental validation using this library. In the last application, the mobile robot successfully follows a colored object using two low-cost cameras (to increase the robot’s field of view) and includes a third camera on top of a servo-driven turret for tracking a second independent object while following the first one in parallel. Resource consumption of all applications has been measured and compared with state-of-the-art proprietary toolchains, revealing that reconfigurable computing with open FPGAs using open tools is now an attractive alternative to designing and creating intelligent vision-based robotic applications using vendor-dependent proprietary tools and FPGAs.

HADES: An NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures

Network Function Virtualization (NFV) aims to replace traditional network functions running in proprietary hardware with software instances (i.e., Virtual Network Functions, VNFs) embedded in general-purpose virtualization solutions. Aware that the transition to a fully virtualized network infrastructure will pay a high energy cost, especially in IoT systems composed of a myriad of devices, energy efficiency is one of the key innovative targets of future networks. Edge computing should be considered in IoT environments to save time and energy by processing data near the producer devices. However, applying NFV in the context of IoT/Edge/Cloud environments complicates the placement of VNFs, due to the inherent heterogeneous nature of such environments and the variety of resource demands. This paper proposes an energy-aware placement of service function chains of VNFs and a resource-allocation solution for heterogeneous edge infrastructures that considers the computation and communication delays according to the VNFs’ location in the infrastructure. The solution has been integrated with the ETSI-sponsored project Open Source Management and Orchestration (OSM) as an extension called HADES, which allows the configuration of VNFs and their subsequent resource allocation and deployment at the edge, minimizing energy consumption and ensuring a quality of service. We have applied the deployment of augmented reality services in real and simulated scenarios. The results show up to a 59% reduction in power consumption and QoS compliance in all scenarios considered compared to default OSM placement and four other allocation policies. We prove that our solution has negligible power overhead, and validate the scalability and applicability of HADES.

Enabling Efficient Spatio-Temporal GPU Sharing for Network Function Virtualization

By leveraging standard IT virtualization technology and Commercial-Off-The-Shelf (COTS) servers, Network Function Virtualization (NFV) decouples network functions from proprietary hardware devices for flexible service provisioning. But the potential of NFV is significantly limited by its performance inefficiency. With the unparalleled advantages of multi-core parallelism and high memory bandwidth, Graphics Processing Units (GPUs) are regarded as a promising way to accelerate Virtualized Network Functions (VNF). However, the special architecture of GPU brings new challenges to task scheduling and resource allocation. To this end, we propose a <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</b> PU <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</b> riented <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</b> patio- <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</b> emporal sharing framework for NFV called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Gost</i> , aiming for GPU based VNF performance promotion. The execution order and GPU resource allocation (i.e., the number of threads) are considered in task scheduling to minimize the end-to-end latency for VNF flows. First, we formulate the task scheduling problem into a nonlinear programming form, and then transform it into an equivalent Integer Linear Programming (ILP) form.The problem is proved as NP-hard. We customize the classical list scheduling algorithm and propose a List Scheduling based Spatio-Temporal GPU sharing strategy (LSSTG), whose achievable worst-case performance is also formally analyzed. We practically implement <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Gost</i> prototype, based on which extensive experiments verify the high performance efficiency of LSSTG compared to state-of-the-art in terms of latency and throughput.

OpenFrame: A modular, sustainable, open microscopy platform with single-shot, dual-axis optical autofocus module providing high precision and long range of operation.

'openFrame' is a modular, low-cost, open-hardware microscopy platform that can be configured or adapted to most light microscopy techniques and is easily upgradeable or expandable to multiple modalities. The ability to freely mix and interchange both open-source and proprietary hardware components or software enables low-cost, yet research-grade instruments to be assembled and maintained. It also enables rapid prototyping of advanced or novel microscope systems. For long-term time-lapse image data acquisition, slide-scanning or high content analysis, we have developed a novel optical autofocus incorporating orthogonal cylindrical optics to provide robust single-shot closed-loop focus lock, which we have demonstrated to accommodate defocus up to ±37μm with <200nm accuracy, and a two-step autofocus mode which we have shown can operate with defocus up to ±68μm. We have used this to implement automated single molecule localisation microscopy (SMLM) in a relatively low-cost openFrame-based instrument using multimode diode lasers for excitation and cooled CMOS cameras.

Open Science Hardware for Realising Globally Equitable Knowledge Production

Physical hardware underpins research in many disciplines. From computing devices, scientific instrumentation, and biological reagents, to remote sensing satellites, researchers rely on hardware to explore and understand the world. However, research equipment is typically based on closed source (i.e. proprietary) hardware, whose designs are legally restricted, preventing others from studying, building, or modifying them. These restrictions cause several problems such as: lack of reproducibility; duplication of effort; forced obsolescence; and higher costs.&#x0D; Crucially, the inefficiencies of closed source hardware reinforce global inequities. This is because the design and manufacturing of research equipment is often monopolised by producers in the Global North. Restricted access to hardware designs mean that only authorised dealers and technicians are allowed to sell or maintain equipment. These services are often unavailable to, or prohibitively expensive for, researchers belonging to historically marginalised communities outside of the Global North.&#x0D; Building on the success of open source software, open source hardware is defined as any physical artefact whose “design is made publicly available with explicit, legally binding freedoms for anyone to study, modify, distribute, make, and sell the design or hardware based on that design”. Open science hardware is an emerging field of practice which studies and applies the principles of open source hardware to research contexts. In 2021, it was formally recognised as a key component in the UNESCO Recommendation on Open Science. Open science hardware provides many benefits compared to its proprietary counterparts. This can include cost savings of up to 87% (Pearce, 2020) and proportional to how often it is replicated; quicker iteration of designs; and adaptation to local needs in underserved communities.&#x0D; Since the 2010s, open science hardware has been developed and used in diverse domains from environmental monitoring, and lab automation, to microscopy. In addition to academics, open science hardware is commonly built by citizen science communities and adapted for different purposes. Other practitioners of open science hardware include educators, social innovators, or artists.&#x0D; In this talk, we provide an overview of open science hardware and the problems it solves. We also provide successful examples of open science hardware projects that serve to not only do good science, but also address global inequities. The talk also presents the Gathering for Open Science Hardware, an international network working towards the adoption of open source hardware across research lifecycle.&#x0D;

A Survey on Rerouting Techniques with P4 Programmable Data Plane Switches

Traditionally, the networking industry has been dominated by closed and proprietary hardware and software. Vendors have been controlling the network by hard-coding how packets should be processed and providing the network operators with a set of predefined protocols. Recently, the industry, operators, and the research community have started to pay special attention to data plane programmability, which allows the user to define the packet processing behavior. Allowing the network operators and programmers to define, deploy, and test new forwarding behaviors in a relatively short time paved the way for a significant wave of innovation and experimentation. With the emergence of programmable data planes, traffic rerouting has been used by the research community. Rerouting approaches are deployed to mitigate various network issues. Despite the considerable number of works that deploy innovative rerouting mechanisms using programmable switches, the literature lacks a comprehensive survey. To this end, this paper provides an in-depth overview, detailed analysis, and unique categorization of the recent programmable data plane-based rerouting approaches. The survey explains the need for rerouting by highlighting the promising results while dealing with link/node failures, load imbalance, and congestion. It then discusses the challenges and considerations and presents future perspectives and open research issues.

Truthful VNFI Procurement Mechanisms With Flexible Resource Provisioning in NFV Markets

With the rapid development of network function virtualization (NFV), more and more enterprises and operators are seeking network service provisioning via service chains of virtual network functions (VNFs), instead of depending on proprietary hardware appliances. Following this trend, an NFV market is emerging, where users can procure different VNF instances (VNFIs) and their combinations from multiple network service providers (NSPs) in a pay-as-you-go way. In such a procurement process, how to guarantee truthfulness while enabling flexible resource provisioning in form of VNFIs is a significant challenge. In this paper, we propose a truthful reverse combinatorial auction-based mechanism to solve the combinatorial VNFI procurement problem. To support flexible resource provisioning, this mechanism allows NSPs to be multi-minded, and determine the provisioning VNFIs according to the auction results. Specifically, we design a heuristic algorithm to determine the winning bids in polynomial time. Furthermore, we devise a critical-payment-based pricing algorithm to induce NSPs to disclose their real costs, aiming to achieve truthfulness. Rigorous theoretical analysis shows the proposed mechanism can guarantee truthfulness, individual rationality and computational efficiency. Simulation results also verify the effectiveness and efficiency of the proposed mechanism.

Cognitive Software Defined Networking and Network Function Virtualization and Applications

The emergence of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has revolutionized the Internet. Using SDN, network devices can be controlled from a centralized, programmable control plane that is decoupled from their data plane, whereas with NFV, network functions (such as network address translation, firewall, and intrusion detection) can be virtualized instead of being implemented on proprietary hardware. In addition, Artificial Intelligence (AI) and Machine Learning (ML) techniques will be key to automating network operations and enhancing customer service. Many of the challenges behind SDN and NFV are currently being investigated in several projects all over the world using AI and ML techniques, such as AI- and software-based networking, autonomic networking, and policy-based network management. Contributions to this Special Issue come from the above areas of research. Following a rigorous review process, four excellent articles were accepted that address and go beyond many of the challenges mentioned above.

Guest Editorial: Machine Learning-Enabled Zero Touch Networks

With the continued growth of IoT devices and their deployment, manually managing and connecting them is impractical and presents multiple challenges. To that end, zero touch networks (ZTNs), which rely on software-based modules instead of dedicated proprietary hardware, become a viable potential solution. The overall aim of ZTNs is for machines to learn how to become more autonomous so that we can delegate complex, mundane tasks to them. Thus, ZTNs are able to monitor networks and services and act on faults with minimal (if any) human intervention, including the early detection of emerging problems, autonomous learning, autonomous remediation, decision making, and support of various optimization objectives. As a result, ZTNs are able to offer self-serving, self-fulfilling, and self-assuring operations.

Low-cost Magnetic Resonance Console Architecture using an Open Source for Laboratory Scale Systems

MRI systems with proprietary hardware must use pulse programming, which is less expensive. Pulse programming consoles use Digital Signal Processor, Complex Programming Logic Device, and microcontrollers, which are typically restricted to particular architectures. General–purpose, extremely affordable electronics board featuring these architectures are now capable enough to be directly implemented in MRI consoles. Here we present the architectural details of various consoles with novel designs and their limitations. Finally, we propose a console design which was created utilising widely accessible Arduino Boards to connect to Pulseq-GPI implementations at a reduced cost of $225

Empowering Network Security With Programmable Switches: A Comprehensive Survey

With the growth of network applications such as 5G and artificial intelligence, network security techniques, i.e., the techniques that detect various attacks (e.g., well-known denial-of service (DDoS) attacks) and prevent production networks (e.g., data center networks) from being attacked, become increasingly essential for network management and have gained great popularity in the networking community. Generally, these techniques are built on proprietary hardware appliances, i.e., middleboxes, or the paradigm that combines both software-defined networking (SDN) and network function virtualization (NFV) to implement security functions. However, the techniques built on middleboxes are proven to be hard-to-manage, costly, and inflexible, thereby making them an out-of-date choice in network security. For the techniques built on SDN and NFV, they virtualize and softwarize security functions on commodity servers, leading to non-trivial performance degradation. Fortunately, the recent emergence of programmable switches brings new opportunities of empowering network security techniques with the characteristics of easy-tomanage, low cost, high flexibility, and Tbps-level performance. In this survey, we focus on this promising trend in network security. More precisely, this survey first presents the preliminaries of programmable switches, which are the primary driver of next-generation network security techniques. Next, we comprehensively review existing techniques built on programmable switches, classify these techniques, and discuss their background, motivation, design, implementation, and limitations case-by-case. Finally, we summarize open issues and future research directions in this promising research topic of network security.