Are your lights off? Using problem frames to diagnose system failures

This paper reports on our experience of investigating the role of software systems in the power blackout that affected parts of the United States and Canada on 14 August 2003. Based on a detailed study of the official report on the blackout, our investigation has aimed to bring out requirements engineering lessons that can inform development practices for dependable software systems. Since the causes of failures are typically rooted in the complex structures of software systems and their world contexts, we have deployed and evaluated a framework that looks beyond the scope of software and into its physical context, directing attention to places in the system structures where failures are likely to occur. We report that (i) Problem Frames were effective in diagnosing the causes of failures and documenting the causes in a schematic and accessible way, and (ii) errors in addressing the concerns of biddable domains, model building problems, and monitoring problems had contributed to the blackout

Integrated Systems Health Management (ISHM) Toolkit

A framework of software components has been implemented to facilitate the development of ISHM systems according to a methodology based on Reliability Centered Maintenance (RCM). This framework is collectively referred to as the Toolkit and was developed using General Atomics' Health MAP (TM) technology. The toolkit is intended to provide assistance to software developers of mission-critical system health monitoring applications in the specification, implementation, configuration, and deployment of such applications. In addition to software tools designed to facilitate these objectives, the toolkit also provides direction to software developers in accordance with an ISHM specification and development methodology. The development tools are based on an RCM approach for the development of ISHM systems. This approach focuses on defining, detecting, and predicting the likelihood of system functional failures and their undesirable consequences

Development of Distributed Research Center for analysis of regional climatic and environmental changes

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far

Web based system architecture for long pulse remote experimentation

Remote experimentation (RE) methods will be essential in next generation fusion devices. Requirements for long pulse RE will be: on-line data visualization, on-line data acquisition processes monitoring and on-line data acquisition systems interactions (start, stop or set-up modifications). Note that these methods are not oriented to real-time control of fusion plant devices. INDRA Sistemas S.A., CIEMAT (Centro de Investigaciones Energéticas Medioambientales y Tecnológicas) and UPM (Universidad Politécnica de Madrid) have designed a specific software architecture for these purposes. The architecture can be supported on the BeansNet platform, whose integration with an application server provides an adequate solution to the requirements. BeansNet is a JINI based framework developed by INDRA, which makes easy the implementation of a remote experimentation model based on a Service Oriented Architecture. The new software architecture has been designed on the basis of the experience acquired in the development of an upgrade of the TJ-II remote experimentation system

Clinical Data Entry & Protocol Tracking System

CLINICAL DATA ENTRY & PROTOCOL TRACKING SYSTEM (CDEPT) is a software framework designed to provide the tools necessary to rapidly develop web based data entry and data management systems for clinical trails and medical research studies. A software framework defines a model, approach, procedures and tools for creating new protocols for clinical studies. As a framework this software is able to gain efficiency by providing standard approaches and tools for commonly needed capabilities such as construction of data entry routines, validation of data, audit trails and monitoring the completeness and timeliness of data collection. However, as a framework this software provides far greater flexibility, expandability and customization than is typical in a turnkey or off the shelf application. CDEPT is designed around a three-tiered software development model widely used on Internet. This model consists of browsers, web server and database servers. This software is mostly designed to run on two major browsers Internet Explorer and Netscape

Mission Tasking, Path Planning, and System Integration for an Autonomous Surface Vessel

This thesis presents the design and development of a fully autonomous surface vessel for use as a research platform for the Office of Naval Research and as a competition entry to the International Maritime RobotX Challenge in 2014 and 2016. The author’s contributions to this include the development of safety systems, power distribution systems, communications software, tasking software, and planning algorithms. The results of these developments include a hardware based safety system, a modular power and health monitoring system, an easy to use autoconfiguring inter-process communications stack, a dynamic tasking engine, and a comparison of two solutions to planning with a kinodynamically constrained vehicle. Several recommendations are made for future work including combining the two planning algorithms and expanding the tasking framework to include multiple vehicles

Diagnosis and Prognosis of Weapon Systems

The Prognostics Framework is a set of software tools with an open architecture that affords a capability to integrate various prognostic software mechanisms and to provide information for operational and battlefield decision-making and logistical planning pertaining to weapon systems. The Prognostics NASA Tech Briefs, February 2005 17 Framework is also a system-level health -management software system that (1) receives data from performance- monitoring and built-in-test sensors and from other prognostic software and (2) processes the received data to derive a diagnosis and a prognosis for a weapon system. This software relates the diagnostic and prognostic information to the overall health of the system, to the ability of the system to perform specific missions, and to needed maintenance actions and maintenance resources. In the development of the Prognostics Framework, effort was focused primarily on extending previously developed model-based diagnostic-reasoning software to add prognostic reasoning capabilities, including capabilities to perform statistical analyses and to utilize information pertaining to deterioration of parts, failure modes, time sensitivity of measured values, mission criticality, historical data, and trends in measurement data. As thus extended, the software offers an overall health-monitoring capability

Intelligent Sensors: Strategies for an Integrated Systems Approach

This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS)

Semantic Caching Framework: An FPGA-Based Application for IoT Security Monitoring

Security monitoring is one subdomain of cybersecurity which aims to guarantee the safety of systems, continuously monitoring unusual events. The development of Internet Of Things leads to huge amounts of information, being heterogeneous and requiring to be efficiently managed. Cloud Computing provides software and hardware resources for large scale data management. However, performances for sequences of on-line queries on long term historical data may be not compatible with the emergency security monitoring. This work aims to address this problem by proposing a semantic caching framework and its application to acceleration hardware with FPGA for fast- and accurate-enough logs processing for various data stores and execution engines

Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services

This paper presents the development of ICAROUS-2 (Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services), the second generation of a software architecture that integrates several algorithms as distributed onboard services to enable robust autonomous UAS applications. In particular, the ICAROUS architecture defines a framework to perform detect and avoid, geofencing, path monitoring, path planning, and autonomous decision making to ensure safety and mission progress. Most of the core algorithms implemented in ICAROUS are formally verified using an interactive theorem prover. These algorithms are composed together using a plan execution engine, whose operational semantics is formally specified. A description of the integrated architecture, services currently available, and flight test results highlighting the capability of ICAROUS are presented