Modeling repairable system failure data using NHPP realiability growth mode.

Stochastic point processes have been widely used to describe the behaviour of repairable systems. The Crow nonhomogeneous Poisson process (NHPP) often known as the Power Law model is regarded as one of the best models for repairable systems. The goodness-of-fit test rejects the intensity function of the power law model, and so the log-linear model was fitted and tested for goodness-of-fit. The Weibull Time to Failure recurrent neural network (WTTE-RNN) framework, a probabilistic deep learning model for failure data, is also explored. However, we find that the WTTE-RNN framework is only appropriate failure data with independent and identically distributed interarrival times of successive failures, and so cannot be applied to nonhomogeneous Poisson process

Optimal configuration of a power grid system with a dynamic performance sharing mechanism

Performance sharing is an effective policy for a power grid system to satisfy the power demand of different districts to greatest extent. Through transmission lines, the districts with sufficient power can share the redundant power with the districts with power deficit. The existing research has incorporated the performance sharing mechanism into systems with simple structures such as parallel systems and series-parallel systems. However, little concentration has been spent on more complex structures. This necessitates the need of this paper that models a power distribution with a more complex reliability structure. We assume that the system is composed of generators and nodes. Both the performance of each generator and the demand of each node in the network are assumed to be random variables. This paper first proposes a dynamic performance sharing policy to minimize the unsupplied demand for a given system with fixed capacity and demand. The optimal allocation of generators, which minimizes the expected system unsupplied demand, is then studied. Numerical examples are proposed to illustrate the applications of the proposed procedures

Methodologies synthesis

This deliverable deals with the modelling and analysis of interdependencies between critical infrastructures, focussing attention on two interdependent infrastructures studied in the context of CRUTIAL: the electric power infrastructure and the information infrastructures supporting management, control and maintenance functionality. The main objectives are: 1) investigate the main challenges to be addressed for the analysis and modelling of interdependencies, 2) review the modelling methodologies and tools that can be used to address these challenges and support the evaluation of the impact of interdependencies on the dependability and resilience of the service delivered to the users, and 3) present the preliminary directions investigated so far by the CRUTIAL consortium for describing and modelling interdependencies

Addressing Complexity and Intelligence in Systems Dependability Evaluation

Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. The first aspect of complexity is the dependability modelling of large systems with many interconnected components and dynamic behaviours such as Priority, Sequencing and Repairs. To address this, the thesis proposes a novel hierarchical solution to dynamic fault tree analysis using Semi-Markov Processes. A second aspect of complexity is the environmental conditions that may impact dependability and their modelling. For instance, weather and logistics can influence maintenance actions and hence dependability of an offshore wind farm. The thesis proposes a semi-Markov-based maintenance model called “Butterfly Maintenance Model (BMM)” to model this complexity and accommodate it in dependability evaluation. A third aspect of complexity is the open nature of system of systems like swarms of drones which makes complete design-time dependability analysis infeasible. To address this aspect, the thesis proposes a dynamic dependability evaluation method using Fault Trees and Markov-Models at runtime.The challenge of “intelligence” arises because Machine Learning (ML) components do not exhibit programmed behaviour; their behaviour is learned from data. However, in traditional dependability analysis, systems are assumed to be programmed or designed. When a system has learned from data, then a distributional shift of operational data from training data may cause ML to behave incorrectly, e.g., misclassify objects. To address this, a new approach called SafeML is developed that uses statistical distance measures for monitoring the performance of ML against such distributional shifts. The thesis develops the proposed models, and evaluates them on case studies, highlighting improvements to the state-of-the-art, limitations and future work

Management: A continuing literature survey with indexes, March 1974

This special bibliography lists 597 reports, articles, and other documents introduced into the NASA scientific and technical information system in 1973

Managed access dependability for critical services in wireless inter domain environment

The Information and Communications Technology (ICT) industry has through the last decades changed and still continues to affect the way people interact with each other and how they access and share information, services and applications in a global market characterized by constant change and evolution. For a networked and highly dynamic society, with consumers and market actors providing infrastructure, networks, services and applications, the mutual dependencies of failure free operations are getting more and more complex. Service Level Agreements (SLAs) between the various actors and users may be used to describe the offerings along with price schemes and promises regarding the delivered quality. However, there is no guarantee for failure free operations whatever efforts and means deployed. A system fails for a number of reasons, but automatic fault handling mechanisms and operational procedures may be used to decrease the probability for service interruptions. The global number of mobile broadband Internet subscriptions surpassed the number of broadband subscriptions over fixed technologies in 2010. The User Equipment (UE) has become a powerful device supporting a number of wireless access technologies and the always best connected opportunities have become a reality. Some services, e.g. health care, smart power grid control, surveillance/monitoring etc. called critical services in this thesis, put high requirements on service dependability. A definition of dependability is the ability to deliver services that can justifiably be trusted. For critical services, the access networks become crucial factors for achieving high dependability. A major challenge in a multi operator, multi technology wireless environment is the mobility of the user that necessitates handovers according to the physical movement. In this thesis it is proposed an approach for how to optimize the dependability for critical services in multi operator, multi technology wireless environment. This approach allows predicting the service availability and continuity at real-time. Predictions of the optimal service availability and continuity are considered crucial for critical services. To increase the dependability for critical services dual homing is proposed where the use of combinations of access points, possibly owned by different operators and using different technologies, are optimized for the specific location and movement of the user. A central part of the thesis is how to ensure the disjointedness of physical and logical resources so important for utilizing the dependability increase potential with dual homing. To address the interdependency issues between physical and logical resources, a study of Operations, Administrations, and Maintenance (OA&M) processes related to the access network of a commercial Global System for Mobile Communications (GSM)/Universal Mobile Telecommunications System (UMTS) operator was performed. The insight obtained by the study provided valuable information of the inter woven dependencies between different actors in the delivery chain of services. Based on the insight gained from the study of OA&M processes a technological neutral information model of physical and logical resources in the access networks is proposed. The model is used for service availability and continuity prediction and to unveil interdependencies between resources for the infrastructure. The model is proposed as an extension of the Media Independent Handover (MIH) framework. A field trial in a commercial network was conducted to verify the feasibility in retrieving the model related information from the operators' Operational Support Systems (OSSs) and to emulate the extension and usage of the MIH framework. In the thesis it is proposed how measurement reports from UE and signaling in networks are used to define virtual cells as part of the proposed extension of the MIH framework. Virtual cells are limited geographical areas where the radio conditions are homogeneous. Virtual cells have radio coverage from a number of access points. A Markovian model is proposed for prediction of the service continuity of a dual homed critical service, where both the infrastructure and radio links are considered. A dependability gain is obtained by choosing a global optimal sequence of access points. Great emphasizes have been on developing computational e cient techniques and near-optimal solutions considered important for being able to predict service continuity at real-time for critical services. The proposed techniques to obtain the global optimal sequence of access points may be used by handover and multi homing mechanisms/protocols for timely handover decisions and access point selections. With the proposed extension of the MIH framework a global optimal sequence of access points providing the highest reliability may be predicted at real-time