Abstract

The 911 emergency response process is a core component of the emergency services critical infrastructure sector in the United States. Modeling and simulation of a complex stochastic system like the 911 response process enables policy makers and stakeholders to better understand, identify, and mitigate the impact of attacks/disasters affecting the 911 system. Modeling the 911 response process as a series of queue sub-systems will enable analysis into how CI failures impact the different phases of the 911 response process. Before such a model can be constructed, the probability distributions of the inter-arrivals of events into these various sub-systems needs to be identified. This research is a first effort into investigating the stochastic behavior of inter-arrival times of different events throughout the 911 response process. I use the methodology of input modeling, a statistical modeling approach, to determine whether the exponential distribution is an appropriate model for these inter-arrival times across a large dataset of historical 911 dispatch records.

Degree

MS

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2020-05-22

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd11143

Keywords

911, emergency response, critical infrastructure protection, statistical modeling, queuing theory, input modeling

Language

English

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