Linux Operating System Research Articles

Achieving High Reliability in Data Acquisition

An urban environment defines a specific micro-climate which directly affects the quality of life in urbanized areas and often has a negative impact on urban populations. Phenomena like urban heat and surface heat islands are direct products of an urban lifestyle. Urban meteorological networks (UMNs) are a tool that can help to better understand and analyze the current situation and make the right decisions about future urban development. Deployed to monitor and record different objects and their states inside urban areas, UMNs build a long-term meteorological data time series database. The most commonly used systems for achieving this goal include wireless sensor networks (WSNs). This paper presents a combined experience in deploying three different WSN systems. During seven years of research in this field, the authors have recognized the importance of data reliability in data acquisition. More importantly, due to the lack of research addressing the reliability of the data received from WSNs by the core segment of the server (processes used in receiving, validating, parsing, and storing data into a database instance), the received data are used in scientific studies without questioning their reliability. To determine the possibility of shifting information provided by the data measured from sensor networks before it is stored in a desired form of database, this paper proposes a highly reliable socket server model. The model is built with high reliability and performance in mind and it includes three major processes, which use a combination of signals and control messages to pass information about their states. A case study is performed using high-end hardware, running a Linux operating system stressed to its limits. Repetition testing revealed inconsistency in the information provided by the operating system to the application layer, which could lead to the loss of information about short-term and rarely occurring monitored objects. The results lead to the conclusion that there is a clear need for a higher level of data reliability in the process of data acquisition by UMNs. The proposed socket server should fill this gap within the server’s core segment.

Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis.

There has been an upward trend in developing frameworks that enable neuroimaging researchers to address challenging questions by leveraging data across multiple sites all over the world. One such open-source framework is the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC) that works on Windows, macOS, and Linux operating systems and leverages containerized analysis pipelines to analyze neuroimaging data stored locally across multiple physical locations without the need for pooling the data at any point during the analysis. In this paper, the COINSTAC team partnered with a data collection consortium to implement the first-ever decentralized voxelwise analysis of brain imaging data performed outside the COINSTAC development group. Decentralized voxel-based morphometry analysis of over 2000 structural magnetic resonance imaging data sets collected at 14 different sites across two cohorts and co-located in different countries was performed to study the structural changes in brain gray matter which linked to age, body mass index (BMI), and smoking. Results produced by the decentralized analysis were consistent with and extended previous findings in the literature. In particular, a widespread cortical gray matter reduction (resembling a 'default mode network' pattern) and hippocampal increase with age, bilateral increases in the hypothalamus and basal ganglia with BMI, and cingulate and thalamic decreases with smoking. This work provides a critical real-world test of the COINSTAC framework in a "Large-N" study. It showcases the potential benefits of performing multivoxel and multivariate analyses of large-scale neuroimaging data located at multiple sites.

Machine-OlF-Action: a unified framework for developing and interpreting machine-learning models for chemosensory research.

Machine Learning-based techniques are emerging as state-of-the-art methods in chemoinformatics to selectively, effectively and speedily identify biologically relevant molecules from large databases. So far, a multitude of such techniques have been proposed, but unfortunately due to their sparse availability, and the dependency on high-end computational literacy, their wider adaptation faces challenges, at least in the context of G-Protein Coupled Receptors (GPCRs)-associated chemosensory research. Here, we report Machine-OlF-Action (MOA), a user-friendly, open-source computational framework, that utilizes user-supplied SMILES (simplified molecular input line entry system) of the chemicals, along with their activation status, to synthesize classification models. MOA integrates a number of popular chemical databases collectively harboring approximately 103 million chemical moieties. MOA also facilitates customized screening of user-supplied chemical datasets. A key feature of MOA is its ability to embed molecules based on the similarity of their local neighborhood, by utilizing a state-of-the-art model interpretability framework LIME. We demonstrate the utility of MOA in identifying previously unreported agonists for human and mouse olfactory receptors OR1A1 and MOR174-9 by leveraging the chemical features of their known agonists and non-agonists. In summary, here we develop an ML-powered software playground for performing supervisory learning tasks involving chemical compounds. MOA is available for Windows, Mac and Linux operating systems. It's accessible at (https://ahuja-lab.in/). Source code, user manual, step-by-step guide and support is available at GitHub (https://github.com/the-ahuja-lab/Machine-Olf-Action). For results, reproducibility and hyperparameters, refer to Supplementary Notes. Supplementary data are available at Bioinformatics online.

ИССЛЕДОВАНИЕ ПОДХОДОВ ДЛЯ АУТЕНТИФИКАЦИИ ПОЛЬЗОВАТЕЛЕЙ БЕСПРОВОДНОЙ СЕТИ С ПРИМЕНЕНИЕМ РАЗЛИЧНЫХ LDAP РЕШЕНИЙ.

Intoduction: every year, the technology of the IEEE802.11 family of networks is becoming more widespread and popular. Based on the possible risks, IT administrators take measures to protect their organizations. One of the ways to improve information security is to use IEEE802.1 x for user authorization. Purpose: the purpose of the study is to study various LDAP solutions for user authorization in a wireless network. Results: three variants of the centralized solution for authorization of users of a wireless network on the basis of operating systems are developed: Windows Server, Ubuntu Linux, and Astra Linux. When working with Windows Server, it was found that you can use the Active Directory LDAP database to store user credentials. The study also showed that if the network infrastructure of the organization needs to implement a server using the Linux operating system, then the FreeIPA database can be used as an LDAP database, and the role of the RADIUS server must be entrusted to the FreeRADIUS software. The advantage of this approach is that all the software required for user authorization is free. Despite the fact that Active Directory is the most popular LDAP database-FreeIPA meets all the needs that arise during security administration. Practical relevance: each solution has passed load testing and can be implemented in the network infrastructure of organizations. Discussion: the choice of operating system and LDAP database for user authorization completely depends on the requirements of the organization, so one of the proposed implementation options will fit each requirement.

Optimal Container Migration for Mobile Edge Computing: Algorithm, System Design and Implementation

Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end-users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, an optimal live migration for containerized edge computing service is studied. This paper presents three zero-downtime migration techniques based on state duplication and state reproduction techniques, and then, proposes an optimal migration technique selection algorithm that jointly minimizes the response time and network traffic during migration. For validation and performance comparison, the proposed migration techniques are implemented on off-the-shelf hardware with Linux operating system. The evaluation results showed that compared with a naive migration, the optimal approach reduced the response time and network load by at least 74.75% and 94.79%, respectively, under considered scenarios.

Design and implementation of neural network computing framework on Zynq SoC embedded platform

Abstract Limited resources and low computing power of embedded platform make it difficult to apply neural network technology. To overcome this problem, a new neural network computing framework “Zynq-Darknet” was proposed. The framework is based on Darknet, which constructs depthwise separable convolution and a lightweight classification model MobileNetV2 and was deployed to Xilinx Zynq-7000 System-on-Chip (SoC) with Linux operating system (OS). In order to verify the performance of the framework and model, experiments were conducted on imagenet-1k dataset using different network structures. The results show that the MobileNetV2 network model based on Zynq-Darknet can effectively perform image classification, and ensure a certain real-time and accuracy while reducing the computational complexity and storage overhead, assuming promising application prospects.

FPGA Prototyping Using the STEMlab Board With Application on Frequency Response Analysis of Electric Machinery

This paper presents a complete procedure on prototyping using the FPGA of the STEMlab board and is intended to serve as a guide for developers, students and researchers interested in speeding up their projects and experiments. Due to the reconfigurability of its internal circuitry, being as simple as a code modification (using hardware description language), FPGA technology allows testing of several controller topologies and/or parameters without the need of any physical change at hardware. This feature allows a much faster development cycle of either commercial products or academic experiments. Besides the reconfigurability of the FPGA, the STEMlab board also offers the advantage of several peripheral already available, which includes, among others, high speed analog-to-digital and digital-to-analog converters, Ethernet communication and a dual-core ARM processor capable of running a Linux operating system. In this paper, a didactic method of use of this board is presented, from getting started to a complete academic and industrial application: detection of early damage on an induction motor using frequency response analysis.

Using the Linux operating system full-time: Tips and experiences from a subject liaison librarian

About a year ago, I requested and received a university libraries issued Ubuntu Linux computer. Ubuntu is a popular open-source GNU/Linux operating system. Since then, I have used Linux every day for all of my liaison librarianship duties, professional service, and scholarship.

Формирование методологии разработки безопасного системного программного обеспечения на примере операционных систем

System software is a cornerstone of any software system, so building secure system software in accordance with requirements of certification authorities and state-of-the-art practices is an important scientific and technical problem. One of possible approaches to cope with the problem is to build a methodology for secure system software development including advanced scientific technologies and industry best practices. The paper presents current results achieved in building such methodology in the following directions. The first one is regulatory framework improvement including development of GOST R specifications defining requirements to formal models of access control policies and their formal verification. The second direction is design and verification of formal models of corresponding security functional requirements. The third direction is application of new and well established technologies of static and run-time analysis of systems software. The considered technologies include static analysis, fuzzing, functional and unit testing as well as testing the system software against formal models of its functional security requirements. The forth direction is development of methods for acquisition of results of all kinds of the analysis and for its analytical processing. All the directions are illustrated by practical examples of application of the methodology to development of Astra Linux operating system distribution that is certified according to the highest evaluation assurance levels.

Open Source Software Supply Chain for Reliability Assurance of Operating Systems

PDF HTML XML Export Cite reminder Open Source Software Supply Chain for Reliability Assurance of Operating Systems DOI: 10.21655/ijsi.1673-7288.00250 Author: Affiliation: Clc Number: Fund Project: Article | Figures | Metrics | Reference | Related | Cited by | Materials | Comments Abstract:Software reliability is one of the research hotspots in the field of software engineering, and failure rate analysis is a typical research method for software reliability. However, the software construction mode has evolved from a single mode to a large-scale collaborative model represented by open source software. As one of the representative products, the operating system includes open source software connected through combinations and dependencies to form a supply network of tens of thousands of nodes. Typical methods lack consideration of supply relationships and cannot accurately identify and evaluate the software reliability issues introduced as a result. This paper extends the concept of supply chain to the field of open source software and proposes a knowledge-based management method for software supply reliability in a collaborative model. The ontological body is designed for the open source software ecosystem firstly, and then the nowledge graph of open source software is constructed to achieve the extraction, storage and management of knowledge; driven by knowledge, combined with traditional supply chain management methods, a set of reliability management methods for open source software supply chain is proposed, which constitutes a management system of open source software supply chain. With the construction of a Linux operating system distribution as an example, the experiment demonstrates how the open source software supply chain supports the reliability of the operating system. Results show that the open source software supply chain will help to clarify and evaluate the reliability risk of large complex system software. Reference Related Cited by

Мониторинг и тестирование модулей операционных систем на основе абстрактных моделей поведения системы

High complexity of a modern operating system (OS) requires to use complex models and high-level specification languages to describe even separated aspects of OS functionality, e.g., security functions. Use of such models in conformance verification of modeled OS needs to establish rather complex relation between elements of OS implementation and elements of the model. In this paper we present a method to establish and support such a relation, which can be effectively used in testing and runtime verification/monitoring of OS. The method described was used successfully in testing and monitoring of Linux OS core components on conformance to Event-B models.

Динамический анализ IoT-систем на основе полносистемной эмуляции в QEMU

The sweeping evolution of the Internet of Things (IoT) requires the development of methods and tools for analyzing such devices. A significant part of similar devices run under operating systems (OS) of the Linux family. Direct application of existing tools for analyzing software (SW) of this class of devices is not always possible. In the process of researching embedded Linux OS, the ELF (embedded linux fuzz) tool was created, which is presented in this work. The article deals with the analysis of systems built exclusively on the basis of Linux kernels. ELF environment is designed for dynamic analysis of devices based on full-system emulation in QEMU. ELF was based on the following aspects: performing software testing and analysis of real devices in an environment as close as possible to their «native» execution environment; integration with existing fuzzing tools; the ability to conduct distributed analysis.

Extraordinary Command Line: Basic Data Editing Tools for Biologists Dealing with Sequence Data

The command line is a standard way of using the Linux operating system. It contains many features essential for efficiently handling data editing and analysis processes. Therefore, it is very useful in bioinformatics applications. Commands allow for rapid manipulation of large ASCII files or very numerous files, making basic command line programming skills a critical component in modern life science research. The following article is not a guide to Linux commands. In this manuscript, in contrast to many various Linux manuals, we aim to present basic command line tools helpful in handling biological sequence data. This manuscript provides a collection of simple and popular hacks dedicated to users with very basic experience in the area of the Linux command line. It includes a description of data formats and examples of editing of four types of data formats popular in bioinformatics applications.

GRACy: A tool for analysing human cytomegalovirus sequence data.

Modern DNA sequencing has instituted a new era in human cytomegalovirus (HCMV) genomics. A key development has been the ability to determine the genome sequences of HCMV strains directly from clinical material. This involves the application of complex and often non-standardized bioinformatics approaches to analysing data of variable quality in a process that requires substantial manual intervention. To relieve this bottleneck, we have developed GRACy (Genome Reconstruction and Annotation of Cytomegalovirus), an easy-to-use toolkit for analysing HCMV sequence data. GRACy automates and integrates modules for read filtering, genotyping, genome assembly, genome annotation, variant analysis, and data submission. These modules were tested extensively on simulated and experimental data and outperformed generic approaches. GRACy is written in Python and is embedded in a graphical user interface with all required dependencies installed by a single command. It runs on the Linux operating system and is designed to allow the future implementation of a cross-platform version. GRACy is distributed under a GPL 3.0 license and is freely available at https://bioinformatics.cvr.ac.uk/software/ with the manual and a test dataset.

FPGA Logic Analyzer

Logical signal analyzer on FPGA - an electronic device that can record and display sequences of digital and analog signals. The task of creating a functional and universal logic analyzer that has the ability to simultaneously capture and analyze 24 digital and 8 analog signals is considered. The ability to connect a display for offline operation with the device, while this factor should not significantly affect the price. The mobility and versatility of the device is ensured thanks to the installed Wi-Fi module, with a server on the board, for remote access. An Ethernet protocol has also been implemented for the ability to work with speeds up to 1 Gbit / s, which will allow you to receive an infinite amount of data without delay and write directly to the computer's memory. The protection of the digital and analog parts from voltage surges, pulse current increase, which could lead to the failure of the circuit and the combustion of the inputs to the processor, has been made.A logic signal analyzer can be used to test and debug digital electronic circuits, for example, when designing computer components and electronic control devices. Unlike oscilloscopes, logic analyzers have much more inputs, but they are not precision and can not be used in research, but this is not necessary for an engineer.In this work, the use of FPGAs is due to the need to ensure a high response rate of the device to a signal change, a programmable integrated matrix is responsible for this. And the other part of the chip with the ARM Cortex A9 processor, which runs the Linux operating system, is responsible for working with peripherals, prioritizing with the simultaneous work of several users. It is possible to modify the device and obtain a fully autonomous and independent device: with its own monitor, information input and output system. There are also possible variations in the construction of the whole test bench, which can not only receive data, but also control processes.

A NEW OPTIMIZED IMPLEMENTATION OF A FAST INTRA PREDICTION MODE DECISION ALGORITHM FOR HEVC STANDARD

New and stronger video compression standard was developed during the last years, called H.265/HEVC (High Efficiency Video Coding). This standard has undergone several improvements compared to H.264/AVC (Advanced Video Coding). In intra prediction block, 33 directional intra prediction modes were included in H.265 to have an efficient coding instead of 8 modes that were used in H.264 in addition to planar and DC modes, which has generated computational complexities in the new standard. Therefore one of the most issues for embedded implementation of HEVC is time reduction of the encoding process. In this paper, an embedded implementation of a fast intra prediction algorithm is performed on ARM processors under the embedded Linux Operating System. Experimental results included the comparison between the original HM16.7 and the proposed algorithm show that the encoding time was reduced by an average of 61.5% with an increase of 1.19 in the bit rate and a small degradation in the PSNR of 0.05%.

BCL::Conf: Improved Open-Source Knowledge-Based Conformation Sampling Using the Crystallography Open Database.

We previously described BCL::Conf, a knowledge-based conformation sampling algorithm utilizing a small molecule fragment rotamer library derived from the Cambridge Structural Database (CSD, license required), as a component of the BioChemical Library (BCL) cheminformatics toolkit. This paper describes substantial improvements made to the BCL::Conf algorithm and a transition to a rotamer library derived from molecules in the Crystallography Open Database (COD, no license required). We demonstrate the performance of the new BCL::Conf on native conformer recovery in the Platinum dataset of high-quality protein-ligand complexes. This set of 2859 structures has previously been used to assess the performance of over a dozen conformer generation algorithms, including the Conformator, Balloon, RDKit DG, ETKDG, Confab, Frog2, MultiConf-DOCK, CSD conformer generator, ConfGenX-OPSL3 force field, Omega, excalc, iCon, and MOE. These benchmarks suggest that the CSD conformer generator is at the state of the art of reported conformer generators. Our results indicate that the improved BCL::Conf significantly outperforms the CSD conformer generation algorithm at binding conformer recovery across a range of ensemble sizes and with similarly fast rates of conformer generation. BCL::Conf is now distributed with the COD-derived rotamer library and is free for academic use. The BCL can be downloaded at http://meilerlab.org/bclcommons for Windows, Linux, or Apple operating systems. BCL::Conf can now also be accessed via webserver at http://meilerlab.org/bclconf.

Analysis and Evaluation of MPLS Network Performance

Currently, the increasing network connectivity is becoming more and more complex and the integration of several services continues to appear. These approaches need a guarantee in terms of throughput, the performance of which they potentially impact. So, the basic aim of this research is to get the best MPLS network performance towards linux and FreeBSD operating systems. This is why in this report, we have worked on MPLS network performance, which will help to identify performance metrics. To evaluate the performance, we used those operating systems implementing the MPLS architecture in order to define the best performing between the two on this domain. For this, we used scapy to measure the response times by varying the size of the packets sent and validate the measurements with the MATLAB Simulink. After all experiments, we realized that FreeBSD operating system is more reliable than linux in MPLS network base.

COTS-Based Real-Time System Development: An Effective Application in Pump Motor Control

The progress of embedded control systems in the last several years has made possible the realization of highly-effective controllers in many domains. It is essential for such systems to provide effective performance at an affordable cost. Furthermore, real-time embedded control systems must have low energy consumption, as well as be reliable and timely. This research investigates primarily the feasibility of implementing an embedded real-time control system, based on a low-cost, commercially off-the-shelf (COTS) microcontroller platform. It explores real-time issues, such as the reliability and timely response, of such a system implementation. This work presents the development and performance evaluation of a novel real-time control architecture, based upon a BeagleBoard microcontroller, and applied into the PWM (pulse width modulation) control of a three-phase induction motor in a suction pump. The approach followed makes minimal use of general-purpose hardware (BeagleBone Black microcontroller board) and open-source software components (including Linux Operating System with PREEMPT_RT real-time support) for building a reliable real-time control system. The applicability of the proposed control system architecture is validated and evaluated in a real case study in manufacturing. The results provide sufficient evidence of the efficiency and reliability of the proposed approach into the development of a real-time control system based upon COTS components.

A study on windows-based ransomware implications on linux operating system using compatibility layer wine based on dynamic analysis

Linux is an open source operating system that uses the Linux kernel. The security of Linux makes its users rarely use antivirus to prevent the threat of ransomware attacks. The purpose of this study is to assess the security of the Linux operating system that uses Wine as a compatibility layer against ransomware attacks. Then to determine whether ransomware has a higher impact than malware samples in previous studies or not. The methods used on the 30 samples are static analysis to identify samples, and dynamic analysis to determine the implications. From the 30 ransomware samples that can run on the Linux operating system, the results obtained show that 80% affect the registry, 50% affect the file system, 50% affect the service, 70% affect the Network and 60% affect the Process. While overall there are 30% of samples that affect the five existing parameters. The results show that ransomware has relatively high implications for existing parameters, inversely proportional to previous research.