Software approach to hazard detection using on-line analysis of safety constraints

Schroeder, Beth; Schwan, Karsten; Aggarwal, Sudhir

doi:10.1109/reldis.1997.632801

Cited by 11 publications

(6 citation statements)

References 21 publications

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“…In these systems asynchronous streams are the norm, that is, no assumptions about periodicity can be made. Stream detection systems are used to monitor performance, such as in R-GMA [12], Autopilot [23], Gigascope [9], changes in HTML pages, such as in Conquer [18], or safety critical systems, such as dQUOB [24]. Though overlap exists between detection systems and data manipulation systems, the focus of the system drives the kind of support provided to users.…”

Section: Categorizing Data Streams Systemsmentioning

confidence: 99%

Framework for Bringing Data Streams to the Grid

Plale

2004

Scientific Programming

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Abstract. Data streams are a prevalent and growing source of timely data, particularly in the scientific domain. Just as it is common today to read starting conditions such as initial weather conditions, for a scientific simulation from a file, it should be equally as easy to draw starting conditions on-demand from live data streams. But efforts to date to bring streaming data to the grid have lacked generality. In this article we introduce a new model for bringing existing data streams systems onto the grid. The model is predicated on the ability to identify stream systems that meet the criteria of being a "data resource". We establish the criteria in this article, and define a grid service architecture for a data streams resource that leverages standardization efforts in the Global Grid Forum. We discuss key research issues in realizing the data streams model. We are currently developing a prototype of this architecture using our dQUOB system.

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Section: Categorizing Data Streams Systemsmentioning

confidence: 99%

Framework for Bringing Data Streams to the Grid

Plale

2004

Scientific Programming

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“…Our approach is to view data streams as a relational database [32] and, through this conceptualization, gain access to the SQL query language plus an intuitive way of thinking about data streams. Specifically, we view data streams as data sources that can be operated on via a relational database query language.…”

Section: Approach and Contributionsmentioning

confidence: 99%

“…Applications for which dQUOB filtering is particularly well-suited include data flow applications [12] such as scientific visualization, grid applications having external sensors or scientific instruments as input sources [9], and online monitoring for performance or hazard detection [32].…”

Section: High-level System Viewmentioning

confidence: 99%

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Dynamic querying of streaming data with the dQUOB system

Plale

Schwan

2003

IEEE Trans. Parallel Distrib. Syst.

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Abstract-Data streaming has established itself as a viable communication abstraction in data-intensive parallel and distributed computations, occurring in applications such as scientific visualization, performance monitoring, and large-scale data transfer. A known problem in large-scale event communication is tailoring the data received at the consumer. It is the general problem of extracting data of interest from a data source, a problem that the database community has successfully addressed with SQL queries, a time tested, user-friendly way for noncomputer scientists to access data. By leveraging the efficiency of query processing provided by relational queries, the dQUOB system provides a conceptual relational data model and SQL query access over streaming data. Queries can be used to extract data, combine streams, and create new streams. The language augments queries with an action to enable more complex data transformations such as Fourier transforms. The dQUOB system has been applied to two large-scale distributed applications: a safety critical autonomous robotics simulation and scientific software visualization for global atmospheric transport modeling. In this paper, we present the dQUOB system and the results of performance evaluation undertaken to assess its applicability in data-intensive wide-area computations, where the benefit of portable data transformation must be evaluated against the cost of continuous query evaluation.

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“…Software agents have proved to be valuable resources as deployed in many critical mission projects [43]. Specifically, agents have been used in hazard detection [37], crisis management [2], risk management [25], space control [10], control of power grid [38] and prevention of bio-attacks [9]. In order to specify and model parallel and concurrent execution of processes, a combination of Pi-calculus and Pi-ADL is used, as this technique provides major support for such kind of concurrent and distributed applications [32].…”

Section: Introductionmentioning

confidence: 99%

Modeling high assurance agent-based Earthquake Management System using formal techniques

et al. 2009

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Disaster management systems are complex applications due to their distributed and decentralized nature. Various components execute in parallel with high need of coordination with each other. In such applications, interaction and communication issues are difficult to model and implement. In this paper, we have proposed agent-based Earthquake Management System (EMS) which is modeled and analyzed using formal approach. Traditionally, such systems undergo through various transformations starting from requirement models and specification to analysis, design and implementation. A variety of formal approaches are available to specify systems for analyzing their structure and behavior; however, there are certain limitations in using these techniques due to their expressiveness and behavior requirements. We have adopted combination of Pi-calculus and Pi-ADL formal languages to model EMS from analysis to design. The formal approach helps to enhance reliability and flexibility of the system by reducing the redundant information. It reduces chances of 98 S. Sadik et al. errors by explicitly mentioning working flow of information. Additionally, a prototype application is presented as proof of concept in EMS context. We have also evaluated our formal specification by using ArchWare and ABC tools; also, comparison of prototype application with major existing techniques is highlighted.

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Software approach to hazard detection using on-line analysis of safety constraints

Cited by 11 publications

References 21 publications

Framework for Bringing Data Streams to the Grid

Framework for Bringing Data Streams to the Grid

Dynamic querying of streaming data with the dQUOB system

Modeling high assurance agent-based Earthquake Management System using formal techniques

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