عنوان

Model-Driven Situational Awareness in Large-Scale, Complex Systems

شماره

TL49950

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Model-Driven Situational Awareness in Large-Scale, Complex Systems

نام عام مواد

[Thesis]

نام نخستين پديدآور

Arun A. Viswanathan

نام ساير پديدآوران

Neuman, Clifford B.

نام ناشر، پخش کننده و غيره

University of Southern California

تاریخ نشرو بخش و غیره

2015

نام خاص و کميت اثر

191

متن يادداشت

Place of publication: United States, Ann Arbor;

جزئيات پايان نامه و نوع درجه آن

Ph.D.

کسي که مدرک را اعطا کرده

University of Southern California

امتياز متن

2015

متن يادداشت

Situational awareness, or the knowledge of what is going on? to figure out what to do?, has become a crucial driver of the decision-making necessary for effectively managing and operating large-scale, complex systems such as the smart grid. The awareness fundamentally depends on the ability of decision-making entities to convert the low-level operational data from systems into higher-level insights relevant for decision-making and response. Technological advances have enabled monitoring and collection of a wide variety of low-level operational event data from system monitors and sensors, along with several domain-independent tools (e.g. visualization, data mining) and domain-specific tools (e.g. knowledge-driven tools, custom scripts) to assist decision-makers in extracting relevant higher-level insights from the data. But, despite the availability of data and tools to make sense of the data, recent high profile incidents involving large-scale systems such as the North American power blackouts, the disruption of train services in Sydney, Australia, and the malicious shutting down of nuclear centrifuges in Iran, have all been linked to a lack of situational awareness of the decision-makers, which prevented them from taking proactive actions to contain the scale and impact of the incident. A key reason for the lack of situational awareness in each circumstance was the inability of decision-making entities to integrate and interpret the heterogeneous low-level information in a way semantically-relevant to their goals and objectives.

موضوع مستند نشده

Computer science

اصطلاح موضوعی

(UMI)AAI10799519;Applied sciences;Situational awareness

مستند نام اشخاص تاييد نشده

Showalter, Raven Alexandra

مستند نام اشخاص تاييد نشده

Neuman, Clifford B.

مستند نام تنالگان تاييد نشده

University of Southern California

شماره بازیابی

2066822149; 10799519

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y