Modeling situational awareness in network centric systems

Eunice E. Santos, Ananya Ojha, John Koraha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Modeling Situation awareness (SA) in NCO/NCW environments is inherently challenging due to the complexity of the underlying network, highly dynamic nature of processes, and the need for real time analysis. In this paper, we present a performance model for SA using the Network Centric Operations Performance & Prediction (NCO-PP) framework, an established framework for analyzing and predicting performance of NCO/NCW networks. In this paper, we continue to formulate a realistic model that represents dynamism in both the information and network spaces and also their effects on each other. We validate our model via simulations that compare the performance of SA under various information sharing and filtering paradigms. We provide and define a number of relevant performance metrics for SA and show with experimental results that modeling the dynamism in the network lead to superior SA. We also show that the performance of the SA can be significantly improved with proactive resource allocation that takes into account the real time predictions of the future states of the network and the environment.

Original languageEnglish (US)
Title of host publicationDefense Transformation and Net-Centric Systems 2009
DOIs
StatePublished - Sep 10 2009
Externally publishedYes
EventDefense Transformation and Net-Centric Systems 2009 - Orlando, FL, United States
Duration: Apr 14 2009Apr 16 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7350
ISSN (Print)0277-786X

Conference

ConferenceDefense Transformation and Net-Centric Systems 2009
CountryUnited States
CityOrlando, FL
Period4/14/094/16/09

Keywords

  • Complex networks
  • NCO Framework
  • Network centric
  • Performance modeling
  • Situation awareness

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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