Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Overcoming Barriers in Supply Chain Analytics—Investigating Measures in LSCM Organizations

While supply chain analytics shows promise regarding value, benefits, and increase in performance for logistics and supply chain management (LSCM) organizations, those organizations are often either reluctant to invest or unable to achieve the returns they aspire to. This article systematically explores the barriers LSCM organizations experience in employing supply chain analytics that contribute to such reluctance and unachieved returns and measures to overcome these barriers. This article therefore aims to systemize the barriers and measures and allocate measures to barriers in order to provide organizations with directions on how to cope with their individual barriers. By using Grounded Theory through 12 in-depth interviews and Q-Methodology to synthesize the intended results, this article derives core categories for the barriers and measures, and their impacts and relationships are mapped based on empirical evidence from various actors along the supply chain. Resultingly, the article presents the core categories of barriers and measures, including their effect on different phases of the analytics solutions life cycle, the explanation of these effects, and accompanying examples. Finally, to address the intended aim of providing directions to organizations, the article provides recommendations for overcoming the identified barriers in organizations

Condition monitoring of power transformer as part of power plant maintenance process

Power transformer is one of the most critical components for electrical network in power plants. This means that dependability has a big role. At the moment end users allocate resources to power transformer maintenance. Resources for on-line condition monitoring on the other hand are not very significant. Reason for this is that transformers are reliable and long life components. However, failure costs might be very significant and online monitoring is justified from that point of view. This thesis focuses on power transformer online condition monitoring. The goal is to find cost-effective and integrated solution which provides good-enough transformer monitoring. The subject has been studied quite a lot which tells about increasing interest towards the subject and might indicate possible markets for transformer monitoring services. In the beginning research will focus on describing maintenance and condition monitoring related terms. Also goals are defined for different stakeholders applying the Delphi method. The middle part of the work focus on power transformer structure, fault statistics, condition monitoring methods and measurement devices. Also possibilities of condition monitoring are covered. Research results are divided into two different categories. First part of the results will be related to requirements defined for power transformer condition monitoring. Results include requirements for three different ranges of transformer monitoring. Second part of the results contains a specification for pilot project to test power transformer condition monitoring methods and devices.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

PriLok: Citizen-protecting distributed epidemic tracing

Contact tracing is an important instrument for national health services to fight epidemics. As part of the COVID-19 situation, many proposals have been made for scaling up contract tracing capacities with the help of smartphone applications, an important but highly critical endeavor due to the privacy risks involved in such solutions. Extending our previously expressed concern, we clearly articulate in this article, the functional and non-functional requirements that any solution has to meet, when striving to serve, not mere collections of individuals, but the whole of a nation, as required in face of such potentially dangerous epidemics. We present a critical information infrastructure, PriLock, a fully-open preliminary architecture proposal and design draft for privacy preserving contact tracing, which we believe can be constructed in a way to fulfill the former requirements. Our architecture leverages the existing regulated mobile communication infrastructure and builds upon the concept of "checks and balances", requiring a majority of independent players to agree to effect any operation on it, thus preventing abuse of the highly sensitive information that must be collected and processed for efficient contact tracing. This is enforced with a largely decentralised layout and highly resilient state-of-the-art technology, which we explain in the paper, finishing by giving a security, dependability and resilience analysis, showing how it meets the defined requirements, even while the infrastructure is under attack

Development of a Decision Support Tool for the Process of Deciding Inventory Levels : A Study at The Absolut Company

Background: Supply Chain Management is receiving increased attention as companies are trying to remain competitive in a global and challenging environment. An important topic to consider when managing the supply chain is inventory control. Companies today have enormous investments in inventories, which means that there are potential improvements regarding tied up capital in raw materials, work-in-progress and finished goods. There are a variety of tools available in the theory to support the process of determining inventory levels, but these general tools are not suitable for every company. Problem description: This master thesis was conducted at The Absolut Company (TAC) – a large spirits manufacturer. They are responsible for the production of Absolut Vodka, a premium vodka brand. As for any manufacturing company it is crucial that the production constantly has material available to avoid stoppages in the lines. The inventory of the bottle cap, which is one of the materials used in the production process, has historically been kept high to ensure constant supply, but now TAC has started to question if these is managed correctly. Hence, there is a desire from TAC to develop a better understanding of what is affecting the inventory levels. There is also a need for an analytical tool that supports the decision making process related to the inventory levels of the bottle caps. Purpose:The purpose of this master thesis is to investigate which factors affect the inventory levels of bottle caps at TAC and to develop a decision support tool for the process of determining appropriate inventory levels for the bottle caps. Research questions: 1. What factors are affecting the inventory levels at TAC? 2. How do the identified factors affect the inventory levels of bottle caps at TAC? 3. How should a tool for deciding appropriate inventory levels of the bottle caps at TAC be designed? Methodology: The research approach for this thesis is a systems approach and the research is performed inductively. A case study has been chosen as research strategy and the design of the case is single case and single unit of analysis. The system is studied by analyzing both qualitative (interview and observations) and quantitative data (operational data from TAC’s ERP system). The quality of the research is evaluated based on the dimensions reliability and validity. Conclusion: During the analysis it was concluded that the factors affecting the inventory levels at TAC come from the cycle and safety inventory. The identified factors associated with the cycle inventory were supplier lead time, purchase batching and production batching, while the factors affecting the safety inventory were forecast accuracy, quality defects, delivery reliability and delivery dependability. From the analysis it was concluded that the factors purchase batching, forecast error and delivery reliability contributed the most to the inventory levels at TAC. The decision support tool was designed to suggest appropriate inventory levels and to give the user an overview of how much each factor contributes to the inventory. In the tool a baseline scenario, reflecting the current situation, and two alternative scenarios are presented. One scenario shows appropriate inventory levels to cover for the mean error and the other scenario is calculated to cover for the maximum error. The tool also gives the user an overview of all the factors affecting the inventory levels of caps that can be used to spread the information in the company and create understanding across departments. Furthermore, the decision support tool can be used to analyze how improvements or deteriorations of the factors affect the inventory levels, to support TAC’s supply chain department in deciding which improvement project should be prioritized

Online disturbance prediction for enhanced availability in smart grids

A gradual move in the electric power industry towards Smart Grids brings new challenges to the system's efficiency and dependability. With a growing complexity and massive introduction of renewable generation, particularly at the distribution level, the number of faults and, consequently, disturbances (errors and failures) is expected to increase significantly. This threatens to compromise grid's availability as traditional, reactive management approaches may soon become insufficient. On the other hand, with grids' digitalization, real-time status data are becoming available. These data may be used to develop advanced management and control methods for a sustainable, more efficient and more dependable grid. A proactive management approach, based on the use of real-time data for predicting near-future disturbances and acting in their anticipation, has already been identified by the Smart Grid community as one of the main pillars of dependability of the future grid. The work presented in this dissertation focuses on predicting disturbances in Active Distributions Networks (ADNs) that are a part of the Smart Grid that evolves the most. These are distribution networks with high share of (renewable) distributed generation and with systems in place for real-time monitoring and control. Our main goal is to develop a methodology for proactive network management, in a sense of proactive mitigation of disturbances, and to design and implement a method for their prediction. We focus on predicting voltage sags as they are identified as one of the most frequent and severe disturbances in distribution networks. We address Smart Grid dependability in a holistic manner by considering its cyber and physical aspects. As a result, we identify Smart Grid dependability properties and develop a taxonomy of faults that contribute to better understanding of the overall dependability of the future grid. As the process of grid's digitization is still ongoing there is a general problem of a lack of data on the grid's status and especially disturbance-related data. These data are necessary to design an accurate disturbance predictor. To overcome this obstacle we introduce a concept of fault injection to simulation of power systems. We develop a framework to simulate a behavior of distribution networks in the presence of faults, and fluctuating generation and load that, alone or combined, may cause disturbances. With the framework we generate a large set of data that we use to develop and evaluate a voltage-sag disturbance predictor. To quantify how prediction and proactive mitigation of disturbances enhance availability we create an availability model of a proactive management. The model is generic and may be applied to evaluate the effect of proactive management on availability in other types of systems, and adapted for quantifying other types of properties as well. Also, we design a metric and a method for optimizing failure prediction to maximize availability with proactive approach. In our conclusion, the level of availability improvement with proactive approach is comparable to the one when using high-reliability and costly components. Following the results of the case study conducted for a 14-bus ADN, grid's availability may be improved by up to an order of magnitude if disturbances are managed proactively instead of reactively. The main results and contributions may be summarized as follows: (i) Taxonomy of faults in Smart Grid has been developed; (ii) Methodology and methods for proactive management of disturbances have been proposed; (iii) Model to quantify availability with proactive management has been developed; (iv) Simulation and fault-injection framework has been designed and implemented to generate disturbance-related data; (v) In the scope of a case study, a voltage-sag predictor, based on machine- learning classification algorithms, has been designed and the effect of proactive disturbance management on downtime and availability has been quantified