Hardware Software Research Articles

Leveraging Distributed Systems for Fault-Tolerant Cloud Computing: A Review of Strategies and Frameworks

Ensuring system availability and reliability is crucial in the quickly developing field of cloud computing. The importance of fault tolerance in cloud infrastructure systems grows as organizations become more reliant on it to support their critical operations. The purpose of this article is to investigate the intricate realm of cloud computing and distributed systems. Specifically, the paper will investigate the numerous forms of cloud computing, fault tolerance methods, and frameworks that enable cloud services to be robust and durable. Cloud computing has transformed the way in which organizations and individuals access and administer computing resources. The paper discusses several deployment options, including public, private, hybrid, and multi-cloud environments, which provide organizations with the advantages of flexibility, scalability, and cost-effectiveness. The inherent flexibility of cloud computing renders it well-suited for a diverse range of applications, spanning from the hosting of websites to the execution of intricate data analytics processes. Generally, cloud computing encounters substantial obstacles, including the need of maintaining uninterrupted service in the face of hardware failures, network outages, or software errors, despite its tremendous benefits. The critical importance of fault tolerance in this particular situation cannot be overstated, as it plays a pivotal role in maintaining the dependability and availability of the system. The primary objective of this study is to examine the utilization of distributed systems as a means to augment fault tolerance within the realm of cloud computing and distributed systems. Distributed systems offer an optimal approach for addressing difficulties related to fault tolerance, owing to its intrinsic capability to divide workloads and data over several nodes. This approach utilizes redundancy, replication, and the ability to recover seamlessly from disturbances, hence enhancing the resilience and resource efficiency of cloud services. This research reviews novel techniques and frameworks that utilize distributed systems to create fault-tolerant cloud computing architectures, emphasizing their substantial influence on the cloud computing domain. In conclusion, this research report includes a comparative analysis table that encompasses twenty preceding works.

Design of ignition control system for failed spacecraft array solid thruster

The life of micro-nano spacecraft is generally short. In order to solve the problem of space debris endangering space safety after its failure and make it deorbit quickly, this paper has carried out the hardware system design and software system design of the ignition control system of the failed spacecraft attitude adjustment solid thruster. In order to facilitate the realization of high integration, the hardware system adopts the array arrangement circuit and selects the MOSFET as the driving switch. The software system receives the ignition command from the spacecraft platform and enables the row and column control terminals of the ignition circuit to achieve addressing ignition. The results show that the control module can correctly receive the instructions from the spacecraft platform and make the correct ignition action, successfully complete the attitude adjustment task, and improve the reliability of the deorbiting of the failed spacecraft.

Design of Improved Ground Closed-loop Test System Based on Variable-stability Flight Control Computer

With the development of civil aviation, ground simulation test has gradually become a key link in the transformation of basic theory to engineering application. By forming a closed-loop link between the variable stability aircraft (VSA) dynamics model and the aircraft rudder surface, sensors, etc., the variable-stability ground closed-loop test system can simulate the aircraft flight state and response characteristics in the ground environment. However, the current ground test system suffers from a wide range of signals, complex signal simulation methods, and low system integration. In this study, an improved modular ground closed-loop test system for VSA is designed from three aspects: signal acquisition and simulation of airborne equipment, parameter monitoring and data processing, and fault simulation subsystem, which improves its compatibility and integrates with the software hardware of the variable-stability flight control computer and other air-borne equipment. After the system interconnection test, the generalized ground closed-loop test system designed in this study can replace the original system more efficiently, and its signal connection has inheritability, and provides a design method reference for other related researches of the variable-stability flight control computer.

SkyLogistics - The Complete Drone Delivery Solution

Abstract: SkyLogistics introduces an innovative drone delivery system aimed at transforming last-mile logistics. Fueled by the growing demand for swift and reliable package delivery solutions, our approach integrates hardware design, software development, and user interface enhancements to deliver seamless experiences. Extensive testing underscores SkyLogistics' exceptional delivery precision, speed, and customer satisfaction while complying with airspace regulations and safety standards. Overcoming challenges like regulatory conformity and scalability, SkyLogistics sets the stage for future advancements in dronebased transportation systems.

EFEKTIVITAS SISTEM INFORMASI AKUNTANSI PENJUALAN (Studi Kasus: UMKM Penggilingan Biji Plastik Masrur Tangerang)

Accounting information systems manage various transaction data, both financial and non- financial, which influence the processing of financial transactions. Effectiveness is a benchmark that describes the extent to which goals are to be achieved. The purpose of this research is to determine the effectiveness of implementing an accounting information system implemented by the Masrur Tangerang Plastic Seed Milling UMKM. This is a qualitative research, and researchers collect data through observation, interviews, and documentation. The results of this research indicate that the sales accounting information system at the Masrur Iron Ore Milling UMKM has been running well and implemented very simply. This is because the system is implemented manually where document archiving is still not optimal and sales invoice documents have not been archived and are still being recorded in MS. Excel. Additionally, effectiveness The accounting information system, seen from an internal control perspective, has not been able to meet the owner's immediate needs. This can be seen from the research findings, which shows that the system used should involve technology by adding hardware components and software components and can also add network components such as WiFi or hotspots so that the resulting accounting information is free from the risk of errors and data backup can be carried out optimally.

USERS SATISFACTION WITH THEIR VR HEADSETS

Virtual Reality (VR) technology has rapidly evolved in recent years, offering immersive experiences that transcend traditional boundaries of entertainment, education, training, healthcare, and various other sectors. At the heart of this technological revolution lies the VR headset, a device that serves as the gateway to virtual worlds. The user satisfaction with VR headsets is a critical aspect that significantly impacts the adoption, acceptance, and success of VR technology as a whole. This dissertation aims to delve deep into understanding the factors influencing user satisfaction with VR headsets, drawing insights from existing literature and empirical studies. By examining the hardware specifications, software content, comfort, usability, and overall experience of VR headsets, this dissertation seeks to contribute to the enhancement of VR technology and user experience.

IoT Based Smart Parking System

Abstract: The IoT-based smart parking system represents an innovative approach to alleviating the prevalent issues of parking shortages and traffic congestion in modern cities. By integrating advanced hardware components and software applications, this system aims to enhance transportation efficiency and sustainability while improving commuter experiences. At its core lies the ESP32 microcontroller, orchestrating data processing from various sensors including parking and traffic IR sensors. These sensors enable real-time monitoring of parking availability and traffic flow, with data seamlessly transmitted to an LCD display for immediate visualization. Additionally, commuters can access this information remotely through a mobile application or web portal, empowering them to make informed travel decisions. The system's standout feature, the smart parking allocation system (SPAS), allows users to locate and reserve parking spaces in advance, effectively reducing the time spent searching for spots and consequently mitigating traffic congestion. Overall, the integration of IoT technology into transportation infrastructure offers a promising solution to the challenges of urban mobility, fostering efficiency, sustainability, and improved commuter satisfaction.

Research on the Application of Three-Dimensional Virtual Reality Technology in Landscape Architecture Design

This study investigates the depth of and engaging experiences for designers and users could transform conventional landscape architecture design approaches through the use of 3D virtual reality technology. Research assesses the advantages and difficulties of using 3D virtual reality (VR) into landscape architectural practice by means of an extensive analysis of the body of current literature and case studies. The study looks into how 3D virtual reality (VR) technology affects the ideation, imagining, collaboration, and presentation phases of the architecture and landscape process of design. It examines how virtual reality simulations can improve communication among design teams, facilitate client engagement, and enhance decision-making processes. The study also looks at the practical and technical aspects of using 3D virtual reality technologies in landscaping design firms, including hardware requirements, software compatibility, and training requirements. In the end, the research's findings deepen our understanding of how 3D virtual reality technology might revolutionize landscape architecture, practice, and spur creative thinking in design processes.

Smart Home Security Design Based on STM32 Microcontroller

This paper addresses the needs in the field of smart home security, based on STM32 microcontroller for smart home security design. Firstly, the background and research significance of smart home security are introduced, and the current situation and development trend of smart home security are briefly summarized. Then, the basic concepts and classifications of microcontrollers are introduced, and the applications and roles of microcontrollers in smart home security are elaborated. Next, the STM32 microcontroller was selected, the system hardware circuit and software program were designed, and the system was implemented and tested. Finally, the research work of this paper is summarized, problems and shortcomings are pointed out, and future research directions and prospects are discussed. Through the research and realization of this paper, the security level of smart home can be effectively improved, and make some contributions to the development of smart home.

Co-design based FPGA implementation of an efficient new speech hyperchaotic cryptosystem in the transform domain

In this paper a new encryption system has been designed and implemented for real-time speech transmission to reduce bandwidth requirements, increase security and minimize residual intelligibility. To guarantee robustness and lightweight computation, the developed cryptosystem has been carried out in the wavelet transform domain based on a hyperchaotic model to generate mask and permutation keys. The cryptographic system has been designed using a hardware-software (HW/SW) co-design approach by developing several IP-cores in a relatively short development time. The performances and security evaluation of the system have been validated through simulation results followed by an experimental validation through the implementation of an encrypted speech signal transmission between two low cost Nexys-4 DDR FPGA platforms, operating in real-time for both wired and wireless communications. Compared to similar works, high performances have been obtained in terms of bandwidth efficiency due to the use of DWT, limited area of FPGA resources, low power consumption and high security level with a large keyspace that is sufficient to resist against brute force attacks. The designed system can be a very useful solution for many real-time secure integrated voice communication systems, multiple communication purposes, military, professional or personal high level of conversations security.

Low-cost desktop learning factory to support the teaching of artificial intelligence

The following document details low-cost hardware and open-source available software tools that can be combined to support active teaching methodologies like Problem-Based Learning (PBL) and incorporate work-oriented technological skills in students. This proposal presents a prototype of Open Educational Resources (OER) that integrates software and hardware tools for the specific purpose of facilitating instruction in Artificial Intelligence. The hardware consists of affordable electronic devices, including an Arduino board, servo motors, sensors, a relay and a motor, all integrated into a scaled conveyor belt. On the other hand, open software was used to implement an image classification program with different features (shape, color, size, among others). The exact construction steps, circuits, and code are presented in detail and should encourage other scientists to replicate the experimental setup, especially if they are looking for experimental teaching of artificial intelligence, since the system allows object classification using the machine learning paradigm to facilitate the teaching of artificial intelligence concepts with computer vision concepts.

Landscape of Digital Technologies Used in the National Health Service in England: Content Analysis.

In England, digital technologies are exploited to transform the way health and social care is provided and encompass a wide range of hardware devices and software that are used in all aspects of health care. However, little is known about the extent to which health care providers differ in digital health technology capabilities and how this relates to geographical and regional differences in health care capacities and resources. This paper aims to identify the set of digital technologies that have been deployed by the National Health Services clinical commissioning groups (NHS CCGs) in England. In doing this, we respond to calls to shed light on the internal dynamics and variation in the form of digital capability in England in terms of health service regional differences and health diversity, equity, and inclusion. We collected 135 annual reports that belong to 106 NHS CCGs in England, comprising more than 18,000 pages in total, released from 2020 to 2021. Using this data set, we identified 2163 pages related to digital technologies and labeled them using content analysis. We follow the construct taxonomy used by digital options theory, a theory from the management information systems field analyzing organizational resource investment choices, in classifying observed technologies according to digital themes-inherent design patterns that we identified and explained. We then used a hierarchical clustering method to extract groups of NHS CCGs that implement similar technology themes. We found 31 technologies from the reports and grouped them into 9 digital themes. The 9 themes were further assigned to 1 of the 3 constructs of digital options theory, the identification of patients' requirements (we identified information portals [76/106], digital health engagement [67/106], and digital inclusion support [45/106]), the development of new work patterns (we identified telehealth [87/106], telemedicine [35/106], and care home technologies [40/106]), the realization of improvements in efficiency and public accessibility (we identified online booking [26/106], online triage [104/106], and digital mental health services [74/106]). The 3 clusters of CCGs are identified based on the 8 themes (Hopkins=0.9914, silhouette=0.186), namely (1) digitally disengaged, (2) digitally engaged, and (3) digital torchbearer. Our findings show prominent digital themes within each construct group, namely information portals, telehealth, and online triage, covering people's fundamental health information needs. Almost half of CCGs fell into the digitally disengaged group, and all London CCGs (5/106) belonged to this group. We propose that practitioners should offer specialized assistance to regions with limited digital engagement, emphasizing digital health literacy, inclusion support, and ongoing evaluation, rather than concentrating solely on technical advancements.

Speed vs. efficiency: A framework for high-frequency trading algorithms on FPGA using Zynq SoC platform

Software-based technical indicators have been widely used for the stock market forecasting, aiming to predict market direction. Even though many algorithms for the software based technical indicators are presented, there are almost no hardware implementations reported in the literature. In this paper, the hardware implementation is presented for three commonly used technical indicators: Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), and Aroon. Latency evaluation is conducted for Bitcoin and Ethereum within a single-day timeframe, utilizing the Xilinx Zynq-7000 programmable SoC XC7Z020-CLG484-1 platform.Additionally, various hardware/software (HW/SW) partitioning strategies are explored to leverage the flexibility of software alongside the performance advantages of hardware via the Zynq SoC platform. The results show that the best performing technical indicator is MACD with a speedup of 30 times over its software only counterpart. Furthermore, a hybrid design integrating multiple technical indicators is proposed, pairing MACD with RSI due to their competitive throughput values, differing by only 0.38 microseconds. This hybrid approach capitalizes on the parallel processing capabilities of hardware, enabling multiple systems to operate simultaneously.

A System for Mixed-Reality Holographic Overlays of Real-Time Rendered 3D-Reconstructed Imaging Using a Video Pass-through Head-Mounted Display-A Pathway to Future Navigation in Chest Wall Surgery.

Background: Three-dimensional reconstructions of state-of-the-art high-resolution imaging are progressively being used more for preprocedural assessment in thoracic surgery. It is a promising tool that aims to improve patient-specific treatment planning, for example, for minimally invasive or robotic-assisted lung resections. Increasingly available mixed-reality hardware based on video pass-through technology enables the projection of image data as a hologram onto the patient. We describe the novel method of real-time 3D surgical planning in a mixed-reality setting by presenting three representative cases utilizing volume rendering. Materials: A mixed-reality system was set up using a high-performance workstation running a video pass-through-based head-mounted display. Image data from computer tomography were imported and volume-rendered in real-time to be customized through live editing. The image-based hologram was projected onto the patient, highlighting the regions of interest. Results: Three oncological cases were selected to explore the potentials of the mixed-reality system. Two of them presented large tumor masses in the thoracic cavity, while a third case presented an unclear lesion of the chest wall. We aligned real-time rendered 3D holographic image data onto the patient allowing us to investigate the relationship between anatomical structures and their respective body position. Conclusions: The exploration of holographic overlay has proven to be promising in improving preprocedural surgical planning, particularly for complex oncological tasks in the thoracic surgical field. Further studies on outcome-related surgical planning and navigation should therefore be conducted. Ongoing technological progress of extended reality hardware and intelligent software features will most likely enhance applicability and the range of use in surgical fields within the near future.

Fully Binarized Graph Convolutional Network Accelerator Based on In‐Memory Computing with Resistive Random‐Access Memory

Artificial intelligence for graph‐structured data has achieved remarkable success in applications such as recommendation systems, social networks, drug discovery, and circuit annotation. Graph convolutional networks (GCNs) are an effective way to learn representations of various graphs. The increasing size and complexity of graphs call for in‐memory computing (IMC) accelerators for GCN to alleviate massive data transmission between off‐chip memory and processing units. However, GCN implementation with IMC is challenging because of the large memory consumption, irregular memory access, and device nonidealities. Herein, a fully binarized GCN (BGCN) accelerator based on computational resistive random‐access memory (RRAM) through software–hardware codesign is presented. The essential operations including aggregation and combination in GCN are implemented on the RRAM crossbar arrays with cooperation between multiply‐and‐accumulation and content‐addressable memory operations. By leveraging the model quantization and IMC on the RRAM, the BGCN accelerator demonstrates less RRAM usage, high robustness to the device variations, high energy efficiency, and comparable classification accuracy compared to the current state‐of‐the‐art GCN accelerators on both graph classification task using the MUTAG and PTC datasets and node classification task using the Cora and CiteSeer datasets. These results provide a promising approach for edge intelligent systems to efficiently process graph‐structured data.

Hybrid cell handover strategy for O-RAN-based campus networks

In recent years, the concept of Open Radio Access Network (O-RAN) has become a prominent and ongoing research area in mobile communications, as mobile operators strive to enhance the intelligence, efficiency, and vendor independence of their RAN (Radio Access Network) architectures and components. O-RAN aims to virtualize and improve RAN functions in software and therefore it supports virtualized RANs where disaggregated network components of multiple vendors are connected via open interfaces. O-RAN is a concept based on interoperability and standardization of RAN elements including a unified interconnection standard for white-box hardware and open-source software elements from different vendors. Architecture integrates a modular base station software stack on off-the-shelf hardware which allows baseband and radio unit components from different suppliers to operate seamlessly together. Analyzing and examining the O-RAN architecture in terms of various network scenarios and different network policies is crucial for next-generation networks. This study begins by discussing the O-RAN architecture and its advantages in detail. Subsequently, a campus network has been proposed for the analysis and simulation of the O-RAN architecture, and performance analyses have been performed within the scope of different scenarios and network policies. As a result of these analysis, a new hybrid algorithm for cell handovers in the O-RAN architecture has been developed and compared with traditional cell handover methods based on Reference Signal Received Power (RSRP) and Quality of Service (QoS). The results indicate that the proposed hybrid handover algorithm for O-RAN architecture yields better outcomes.

ASPEN Study Case: Real Time in Situ Tomato Detection and Localization for Yield Estimation

As the human population continues to grow, our food production system is challenge. With tomato as the main fruit produced indoors, the selection of varieties adapted to specific conditions and higher yields is an imperative task if we are to meet the growing food demand. To assist growers and researchers in the task of phenotyping, we present a study case of the Agroscope phenotyping tool (ASPEN) in tomato. We show that when using the ASPEN pipeline, it is possible to obtain real-time in situ yield estimation without a previous calibration. To discuss our results, we analyse the two main steps of the pipeline in a desktop computer: object detection and tracking, and yield prediction. Thanks to the use of YOLOv5, we obtain a mean average precision for all categories of 0.85, which together with the best multiple object tracking (MOT) tested allow obtaining a correlation value of 0.97 compared to the real number of tomatoes harvested and a correlation of 0.91 when considering the yield thanks to the use of a SLAM algorithm. In addition, the ASPEN pipeline demonstrated to be able of predicting subsequent harvests. Our results demonstrate in situ and real-time size and quality estimation per fruit, which could be beneficial for multiple users. To increase the accessibility and use of new technologies, we make publicly available the necessary hardware material and software to reproduce this pipeline, which includes a dataset of more than 820 relabelled images for the tomato object detection task and the trained weights.

Surface Illumination as a Factor Influencing the Efficacy of Defect Recognition on a Rolled Metal Surface Using a Deep Neural Network

Modern neural networks have made great strides in recognising objects in images and are widely used in defect detection. However, the output of a neural network strongly depends on both the training dataset and the conditions under which the image was acquired for analysis. We have developed a software–hardware method for evaluating the effect of variable lighting on the results of defect recognition using a neural network model. The proposed approach allows us to analyse the recognition results of an existing neural network model and identify the optimal range of illumination at which the desired defects are recognised most consistently. For this purpose, we analysed the variability in quantitative parameters (area and orientation) of damage obtained at different degrees of illumination for two different light sources: LED and conventional incandescent lamps. We calculated each image’s average illuminance and quantitative parameters of recognised defects. Each set of parameters represents the results of defect recognition for a particular illuminance level of a given light source. The proposed approach allows the results obtained using different light sources and illumination levels to be compared and the optimal source type/illuminance level to be figured out. This makes implementing a defect detection environment that allows the best recognition accuracy and the most controlled product quality possible. An analysis of a steel sheet surface showed that the best recognition result was achieved at an illuminance of ~200 lx. An illuminance of less than ~150 lx does not allow most defects to be recognised, whereas an illuminance larger than ~250 lx increases the number of small objects that are falsely recognised as defects.

Pflow: An end-to-end heterogeneous acceleration framework for CNN inference on FPGAs

Field-Programmable Gate Arrays (FPGAs), renowned for their high performance per watt, are extensively utilized to accelerate Convolutional Neural Networks (CNNs) in edge computing environments, primarily employing dataflow-based and instruction set-based approaches. Compared to the instruction set-based approach that features fast and versatile circuit design, the dataflow-based approach can significantly enhance performance at the expense of design versatility. Nevertheless, edge computing environments require both high energy efficiency and adaptability to various scenarios. This paper proposes a novel end-to-end heterogeneous acceleration framework for CNN inference on FPGAs, named Pflow. The basic idea is to decouple network deployment and hardware details with a hardware–software co-design approach. First, a dataflow accelerator with an adaptive scheduling strategy is proposed. The adaptive scheduling strategy, along with a scalable design, maximizes hardware utilization in terms of computing resources and bandwidth. Secondly, we design a novel operator-perception method to automate the processes of network reconstruction and operator fusion. Thirdly, we integrate Pflow into the industrial-grade deep learning framework Paddle-Lite. We evaluate Pflow by implementing several networks on two representative FPGA platforms. Experimental results demonstrate that Pflow achieves energy efficiencies of 46.5 GOPS/W on Xilinx Zynq Ultrascale+ MPSoC 3EG and 59.4 GOPS/W on Virtex UltraScale+ XCVU13P. It also reaches a throughput of up to 255.7 GOPS on the former and 3.686 TOPS on the latter.

A measurement-based approach to analyze the power consumption of the softwarized 5G core

In light of the ever growing energy needs of the ICT sector, a value that is becoming increasingly important for a mobile network is its power consumption. However, the transition away from legacy network deployments tightly coupled with the underlying hardware and the adoption of the Network Function Virtualization (NFV) paradigm has made more difficult to accurately evaluate their energy and carbon footprint. In this paper, we propose and validate a measurement-based approach to analyze the power consumption of a virtualized 5G core network (5GC) deployment. We design an experimental testbed using commercial off-the-shelf (COTS) hardware and open-source software as a sample architecture simulating an edge computing node and supporting three different virtualization options. We make use of both hardware-based and software-based power meters to investigate the power consumption trends associated with increasing levels of traffic and multiple 5GC deployment types. The results show the feasibility of a real-time power monitoring system and highlight how deployment choices, such as virtualization framework and 5GC software, can significantly impact on the power consumption of the network.