Operating System Configuration Research Articles

Design and performance evaluation of Front glass-covered photovoltaics-thermal hybrid system for enhanced electrical output and hot water production

Proof of concept is established for the thermal management of PV modules for the simultaneous benefit of electrical and thermal efficiency. It was achieved by designing the controlled open-loop water-based hybrid PV-T system and demonstrated for thermal management of 150W photovoltaic panel at natural solar conditions. In this integrated front glass-covered PV-T hybrid (IFG-PV-T) system, the PV panel is clipped between the front glass and rear aluminium collector without causing any permanent changes in the existing panel. The flow of water from the source tank is controlled by automated solenoid valve assembly coupled with thermocouples. The solenoid operational temperature is fixed at 40°C to controlled the PV surface temperature at an optimum range to mitigate the adverse effect on voltage and current output. The water layer thickness in the front glass box is optimized to filter the maximum infrared radiations and the collector's toughened glass feature allows the maximum light transmittance with super safety. The performance of the IFG-PV-T system has been evaluated in terms of variation in open circuit voltage, short circuit current, maximum power output, electric and thermal efficiency under the natural solar insolation for a week. Experimental investigations revealed that the open-circuit voltage is increased by ∼16.1 % with IFG-PV-T as compared to conventional PV panel. The increment can be attributed to the synergy of the front glass collector and solenoid valve operation at 40oC that regulates PV surface temperature and boost the current output. These factors have ameliorated the electrical efficiency of IFG-PV-T compared to conventional PV panel. The average thermal efficiency was 39.4 ​% wherein the IFG-PV-T system provides ∼100 ​L of hot water (38–41 ​°C) per day. The present controlled loop operation system and collector configuration have proven their significance for electrical power increment and concomitantly able to deliver moderate hot water which can be useful for any household or commercial application.

Advancing Network Infrastructure: Integrating VXLAN Technology with Automated Circuit Operations and NOS Configurations

Enhancing network infrastructure is achieved through integrating VXLAN technology, Python-automated circuit operations, and Ansible-driven Network Operating System (NOS) configurations, complemented by GitHub for reliable configuration backups. VXLAN, a robust network virtualization protocol, addresses the challenges of managing extensive network segments. Python scripts facilitate the automated analysis, creation, and management of network circuits, significantly boosting efficiency and accuracy. Ansible, a powerful automation tool, is employed to streamline NOS configurations, ensuring consistency and reducing manual overhead in network settings. Concurrently, GitHub, working in tandem with crontab scheduling, offers a dependable platform for the automated, regular backup of configurations, thus enhancing network resilience and simplifying recovery processes. The collective implementation of VXLAN, Python, and Ansible automation, along with GitHub for configuration management, marks a notable advancement in operational efficiency, underscoring their importance as critical components in the modernization and security of network infrastructures.

A Formal Approach to Design and Security Verification of Operating Systems for Intelligent Transportation Systems Based on Object Model

Operating system in intelligent transportation systems (ITSs) is a complex software system whose correctness and security are not obvious. There are advances in formal description and verification of operating systems in ITSs recently and they mainly focus on bottom-up proofs in which the source codes satisfy certain expected properties expressed by logic formulae. In this paper, we propose a layered object model for operating systems in ITSs. This model includes functionality layer, refinement layer and concrete layer. We consider the operating system object model as a logic system ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L)$</tex-math> </inline-formula> with variables representing the objects of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$</tex-math> </inline-formula> , and a series of logic formulae for security and functional configurations in security of ITSs. We establish a mathematical structure as a domain of discourse for operating system in ITSs and accordingly, construct a mapping from operating system objects to the domain. In this way, we propose a formal method to verify the operating system security properties and configurations in ITSs. We use the virtual memory management part of our self-designed operating system VSOS as an example to illustrate the model and show that the claimed security properties can be rigorously proven for ITSs. The evaluation and verification of VSOS indicate that the proposed model implementation is feasible and achieves the security goals.

Optimal design method and benefits research for a regional integrated energy system

Regional integrated energy systems (RIES) have garnered increased attention because they highly utilize renewable energy, comprehensive efficiency, and flexible operation. However, the current research on RIESs is mainly based on burning natural gas and supplemented by renewable energy, which will consumes much primary energy and generates corresponding carbon emissions. Therefore, a RIES contained various renewable energy sources and station energy sharing was constructed in this paper. Both the collaborative optimization model, which considered the operating parameters and system configuration, and the hierarchical optimization model, which optimizes the equipment configuration at the upper layer and the operational parameters at the underlayer, were constructed, respectively. Taking a multi-function low-carbon park as an example, the isolated integrated energy system (IIES) and RIES performances were explored. Finally, the operation cost, carbon emission, and interactive power in the separated production system, IIES and RIES were analyzed and discussed from a long-short time scale perspective. The results showed that the carbon emission, interactive power, and energy supply cost of the RIES's unit area are 7.62 kg/m2, 10.07 kWh/m2, and 40.55 CNY/m2, respectively. Long time scale perspective (Years or months), RIESs could significantly reduce carbon emissions and interactive power. However, on a short time scale viewpoint (Hours), the system's instantaneous energy conservation and carbon reduction effect was general; meanwhile, the maximum grid-connected power in IIES and RIES was 2617.7 and 2712.0 kW, respectively.

Dynamic Context Awareness of Universal Middleware based for IoT SNMP Service Platform

This study focused on the Universal Middleware design for the IoT (Internet of Things) service gateway for the implementation module of the convergence platform. Recently, IoT service gateway including convergence platform could be supported on dynamic module system that is required mounting and recognized intelligent status with the remote network protocol. These awareness concepts support the dynamic environment of the cross-platform distributed computing technology is supported by these idea as a Universal Middleware for network substitution. Distribution system commonly used in recent embedded systems include CORBA (Common Object Request Broker Architecture), RMI (Remote Method Invocation), DCE (Distributed Computing Environment) for dynamic service interface, and suggested implementations of a device object context. However, the aforementioned technologies do not support each standardization of application services, communication protocols, and data, but are also limited in supporting inter-system scalability. In particular, in order to configure an IoT service module, the system can be simplified, and an independent service module can be configured as long as it can support the standardization of modules based on hardware and software components. This paper proposed a design method for Universal Middleware that, by providing IoT modules and service gateways with scalability for configuring operating system configuration, may be utilized as an alternative. This design could be a standardized interface provisioning way for hardware and software components as convergence services, and providing a framework for system construction. Universal Middleware Framework could be presented and dynamic environment standardization module of network protocols, various application service modules such as JINI (Apache River), UPnP (Universal Plug &amp;amp; Play), SLP (Service Location Protocol) bundles that provide communication facilities, and persistence data module. In this IoT gateway, management for based Universal Middleware framework support and available for each management operation, application service component could be cross-executed over SNMP (Simple Network Management Protocol) version 1, version 2, and version 3. The way of SNMP extension service modules are conducted cross-support each module and independent system meta-information that could be built life cycle management component through the MIB (Management Information Base) information unit analysis. Therefore, the MIB role of relation with the Dispatcher applied to support multiple concurrent SNMP messages by receiving incoming messages and managing the transfer of PDU (Protocol Data Unit) between the RFC 1906 network in this study. Results of the study revealed utilizing Universal Middleware that dynamic situations of context objects with mechanisms and tools to publish information could be consisted of IoT to standardize module interfaces to external service clients as a convergence between hardware and software platforms.

Web-based GIS for simulation, and visualisation: EPANET and data-rich shapefiles

The management of water resources often involves with spatially and temporally varied information collected from various providers with different data formats. Although certain software or applications such as QGIS[1] and EPANET[2] have been developed to support the analyses and decision making, these solutions do have some critical weaknesses: 1) it can take users considerable time to become proficient in using a given application, 2) applications generally assume a level of domain-specific knowledge, 3) applications may require customisation through plug-ins to provide suitable information and 4) applications are often tied to specific hardware / operating system configurations. To address these issues, the aqua3s and Fiware4Water research programmes were developed as ‘cloud first’ projects, using the cloud/web to deliver functionality. In this work, we developed approaches for integrating and visualising information to support water management, specifically developing a web-based EPANET simulation and visualisation for large water networks (c30,000 EPANET nodes and links), and a web-based visualisation of regional flood data shapefiles for Trieste and surrounding regions. In both cases, data was processed and balanced between client and server to minimise client loading and maximise responsiveness.

Using Python Modules in Real-Time Plasma Systems for Fusion.

One of the most important applications of sensors is feedback control, in which an algorithm is applied to data that are collected from sensors in order to drive system actuators and achieve the desired outputs of the target plant. One of the most challenging applications of this control is represented by magnetic confinement fusion, in which real-time systems are responsible for the confinement of plasma at a temperature of several million degrees within a toroidal container by means of strong electromagnetic fields. Due to the fast dynamics of the underlying physical phenomena, data that are collected from electromagnetic sensors must be processed in real time. In most applications, real-time systems are implemented in C++; however, Python applications are now becoming more and more widespread, which has raised potential interest in their applicability in real-time systems. In this study, a framework was set up to assess the applicability of Python in real-time systems. For this purpose, a reference operating system configuration was chosen, which was optimized for real time, together with a reference framework for real-time data management. Within this framework, the performance of modules that computed PID control and FFT transforms was compared for C++ and Python implementations, respectively. Despite the initial concerns about Python applicability in real-time systems, it was found that the worst-case execution time (WCET) could also be safely defined for modules that were implemented in Python, thereby confirming that they could be considered for real-time applications.

Advanced and Secure Laboratory Management System

Abstract: Advanced &amp; Secure Laboratory Information Management System, TRLIMS is the management system which has live tracking system for all the testing and research conducted at the laboratory. This system is developed to achieve diverse functionality for the disciplines such as mechanical, chemical, environmental, microbiology and non-destructive fields. The basic features of this application are that it can manage the data related to client, employees and testing results of the laboratory. Apart from that since the application is fully hosted on server which offers flexibility, providing future scope for more hardware and operating system configuration. This application provides very enhanced turn-around-time (TAT) for the material testing laboratory It aims to manage the employees, clients and associated testing data to improve the lab productivity. The application allows clients to track their improvement in sample testing from time to time, the data is updated on server by employees who perform tests at the premises. This paper could provide guidance to understanding the operation mechanism of Laboratory Information Management System.

The Case for Medical Device Cybersecurity Hygiene Practices for Frontline Personnel

The Case for Medical Device Cybersecurity Hygiene Practices for Frontline Personnel

Dynamic response enhancement of BDFIG using vector control scheme based internal model c ontrol

Doublefed induction generator(DFIG) has shown tremendous success inwind turbines due to its flexibility and ability to regulate the active andreactive power. However, the presence of brushes and slip rings affects itsreliability, stability, and power quality. Furthermore, itdoes not providepromising outcomes in case of faults even in presence of the crowbar circuit.In contrast, thebrushless doubly fed induction generator(BDFIG) is a morereliable option for wind turbines than its mentioned counterpart due to theabsence of the brushes and slip rings. This research work as such attempts toimprove the dynamic performance of thevector control(VC)oriented powerwinding (PW) stator flux-based BDFIG by optimally selecting theproportional-integral(PI) gains throughinternalmodel control(IMC)approach. The proposed control scheme is utilized to regulate the speed,torque, and reactive power of the considered BDFIG independently. Contraryto the previous literature where the “trial and error method” is generallyutilized, the current research work uses the IMC for selecting the mostsuitable PI parameters, thus reduces the complexity, time consumption, anduncertainty in optimal selection. The considered BDFIG based wind turbinewith the proposed control scheme provides a better BDFIG control designwith an enhanced dynamic response as compared to that of the same withDFIG under identical operating conditions and system configurations.

Importance Analysis of Components of a Multi-Operational-State Power System Using Fault Tree Models

This article describes a case study using a fault tree analysis for a multi-operational-state system (system with several operational states) model with many different technical solutions for the power system of a fishing vessel. We describe the essence of system dependability metamodeling. A vector of external events was used to construct a detailed metamodel, depending on the operational status being modeled. In a fault tree, individual external events modify the structure of a system. The analysis includes the following operational states: sea voyages of a vessel, hauling in and paying out nets, trawling, staying in a port, and heaving to. For each operational state and assumed system configurations, the importance of system components was determined by calculating the Vesely–Fussell measures. The most important components for each operational state of a system were determined, and the critical system components, that is, those that are important in every operational state and system configuration, were identified.

Coordinated Operation and Planning of Integrated Electricity and Gas Community Energy System With Enhanced Operational Resilience

The coupling in integrated electricity and gas community energy system (IEGS) provides alternative operation modes when unpredictable outages occur at energy-supply sides. Reasonable operation strategies and system configuration can effectively improve the system's resilience, making reliable and continuous operation feasible. Based on the complementary characteristics and reserve capabilities of IEGS, this paper proposes a multi-stage scheduling strategy for resilience enhancement in which thermal storage serves as emergency response resources. The resilient scheduling framework consists of rolling reserve optimization stage, day-ahead economic dispatch stage and fault restoration stage. With the reserve capacity of energy storage generated by rolling optimization and day-ahead dispatch, multiple forms' critical loads will be satisfied in priority when outage occurs on energy-supply sides. Furthermore, a two-level planning model integrating the resilient operation strategy is formulated to better adapt to the source emergency. The proposed planning method is applied to an IEGS with practical demands as a case study. The results show that the configuration generated by the two-level planning model can satisfy the daily reserve requirements for emergency failures, and the resilient scheduling strategy with storage reserve can improve the system resilience effectively.

Frequency Energy Analysis in Detecting Rolling Bearing Faults

Component failure analysis is sometimes difficult to directly detect due to the complexity of an operating system configuration. Raw time series data is not enough in some cases to understand the type of fault or how it is progressing. The conversion of data from the time domain to the frequency domain assists researchers in making a more discernible difference for detecting failures, but depending on the manufacturing equipment type and complexity, there is still a possibility for inaccurate results. This research explores a method of classifying rolling bearing faults utilizing the total energy gathered from the Power Spectral Density (PSD) of a Fast Fourier Transform (FFT). Using a spectrogram over an entire process cycle, the PSD is swept through time and the total energy is computed and plotted over the periodic machine cycle. Comparing with a baseline set of data, classification patterns emerge, giving an indication of the type of fault, when a fault begins and how the fault progresses. There is a separable difference in each type of fault and a measurable change in the distribution of accumulated damage over time. A roller bearing is used as a validating component, due to the known types of faults and their classifications. Traditional methods are used for comparison and the method verified using experimental and industrial applications. Future application is justified for more complex and not so well-understood systems.

Dynamic response enhancement of grid‐tied ac microgrid using salp swarm optimization algorithm

To alleviate the overloads in the power system and to reduce the exponential growth in carbon dioxide (CO2) emissions, deployment of the renewable energy sources (RES) into the power system is the need of the hour. However, injecting these RES into the current power system network causes large voltage and power overshoots hence deteriorate the transient response and power quality of the overall power system. In this paper, an efficient solution of the above-mentioned issues is explored by developing an optimal microgrid (MG) controller using one of the most modern and intelligent artificial intelligence (AI) techniques named the salp swarm optimization algorithm (SSA). The intelligence of the SSA is exploited to select the optimal controller gains and dc-link capacitance value by minimizing a time integrating error fitness function (FF) which in-turn enhances the dynamic response and power quality of the studied MG system. The proposed grid-tied MG controller is designed to achieve the preset active and reactive power sharing ratio between distributed generator (DG) and utility grid during DG and load switching conditions. To validate the superiority of the proposed controller, its performance is compared with that of its precedent grasshopper optimization algorithm (GOA)-based controller for the identical operating conditions and system configuration. The outcomes of the study show that the proposed MG controller outperforms its competitor in terms of transient response and quality of power.

Mystique: A Fine-Grained and Transparent Congestion Control Enforcement Scheme

TCP congestion control is a vital component for the latency of Web services. In practice, a single congestion control mechanism is often used to handle all TCP connections on a Web server, e.g., Cubic for Linux by default. Considering complex and ever-changing networking environment, the default congestion control may not always be the most suitable one. Adjusting congestion control to meet different networking scenarios usually requires modification of TCP stacks on a server. This is difficult, if not impossible, due to various operating system and application configurations on production servers. In this paper, we propose Mystique, a light-weight, flexible, and dynamic congestion control switching scheme that allows network or server administrators to deploy any congestion control schemes transparently without modifying existing TCP stacks on servers. We have implemented Mystique in Open vSwitch (OVS) and conducted extensive test-bed experiments in both public and private cloud environments. Experiment results have demonstrated that Mystique is able to effectively adapt to varying network conditions, and can always employ the most suitable congestion control for each TCP connection. More specifically, Mystique can significantly reduce latency by 18.13% on average when compared with individual congestion controls.

Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid

The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern soft computational optimization algorithms called salp swarm optimization algorithm (SSA) is utilized to select the best combination of the PI gains (kp and ki) and dc side capacitance (C), which in turn ensures optimal transient response during the distributed generator (DG) insertion and load change conditions. Finally, to evaluate the effectiveness of the proposed control approach, its outcomes are compared with that of the previous approaches used in recent literature on basis of transient response measures, quality of solution and power quality. The results prove the superiority of the proposed control scheme over that of the particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) based MG controllers for the same operating conditions and system configuration.

Examining system configuration in an open pit mine design

Current industry practice aims to develop mine designs with a fixed system configuration for a single set of inputs; without regard for uncertainty. Uncertainty is a key element of mining which causes variability in the inputs to the decision making process. Various sources of uncertainty exist in mining projects which may stem from volatility in commodity prices, unknown geological conditions, variable costs or unpredictable productivities. Design approaches that attempt to leverage this uncertainty are proposed and compared in this paper; namely, flexible, robust and operational designs. An analysis of these system configurations reveal that a flexible system configuration generates more value than a robust system configuration, which in turn generates more value than a fixed system configuration. However, a flexible system configuration cannot be practically implemented due to constant change. A robust configuration provides a solution where change can be handled and the analysis of the flexible system configuration provides an optimal frontier (value potential) to compare alternatives. An operational system configuration can be generated by analysing the system configurations generated by flexible and robust design. This paper uses a case study to develop and compare these modelling methodologies and proposes an operational system configuration; as a best fit.

How to Measure the Killer Microsecond

Datacenter-networking research requires tools to both generate traffic and accurately measure latency and throughput. While hardware-based tools have long existed commercially, they are primarily used to validate ASICs and lack flexibility, e.g. to study new protocols. They are also too expensive for academics. The recent development of kernel-bypass networking and advanced NIC features such as hardware timestamping have created new opportunities for accurate latency measurements. This paper compares these two approaches, and in particular whether commodity servers and NICs, when properly configured, can measure the latency distributions as precisely as specialized hardware. Our work shows that well-designed commodity solutions can capture subtle differences in the tail latency of stateless UDP traffic. We use hardware devices as the ground truth, both to measure latency and to forward traffic. We compare the ground truth with observations that combine five latency-measuring clients and five different port forwarding solutions and configurations. State-of-the-art software such as MoonGen that uses NIC hardware timestamping provides sufficient visibility into tail latencies to study the effect of subtle operating system configuration changes. We also observe that the kernel-bypass-based TRex software, that only relies on the CPU to timestamp traffic, can also provide solid results when NIC timestamps are not available for a particular protocol or device.

Reducing audio stimulus presentation latencies across studies, laboratories, and hardware and operating system configurations

Using differing computer platforms and audio output devices to deliver audio stimuli often introduces (1) substantial variability across labs and (2) variable time between the intended and actual sound delivery (the sound onset latency). Fast, accurate audio onset latencies are particularly important when audio stimuli need to be delivered precisely as part of studies that depend on accurate timing (e.g., electroencephalographic, event-related potential, or multimodal studies), or in multisite studies in which standardization and strict control over the computer platforms used is not feasible. This research describes the variability introduced by using differing configurations and introduces a novel approach to minimizing audio sound latency and variability. A stimulus presentation and latency assessment approach is presented using E-Prime and Chronos (a new multifunction, USB-based data presentation and collection device). The present approach reliably delivers audio stimuli with low latencies that vary by ≤1 ms, independent of hardware and Windows operating system (OS)/driver combinations. The Chronos audio subsystem adopts a buffering, aborting, querying, and remixing approach to the delivery of audio, to achieve a consistent 1-ms sound onset latency for single-sound delivery, and precise delivery of multiple sounds that achieves standard deviations of 1/10th of a millisecond without the use of advanced scripting. Chronos's sound onset latencies are small, reliable, and consistent across systems. Testing of standard audio delivery devices and configurations highlights the need for careful attention to consistency between labs, experiments, and multiple study sites in their hardware choices, OS selections, and adoption of audio delivery systems designed to sidestep the audio latency variability issue.

Automotive real-time operating systems

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. Distributed system development, short time-to-market intervals, and automotive safety standards (such as ISO 26262 [8]) require efficient and consistent product development along the entire development lifecycle. The automotive OSEK/VDX standard provides an architecture for distributed real-time units in vehicles and a language aiming in specifying the configuration of real-time OSEK operating systems. The aim of this paper is to enhance a model-driven system-engineering framework with the capability of generating OS configurations from existing high level control system information. Furthermore, to enable the possibility to update stored information from OSEK Implementation Language (OIL) files and support round-trip engineering of real-time operating system (RTOS) configurations. This enables the seamless description of automotive RTOS, from system level requirements to software implementation and therefore ensures consistency and correctness of the configuration. To that aim, a bidirectional tool bridge is proposed based on OSEK OIL exchange format files.