Scheduling Policies for an Antiterrorist Surveillance System

Abstract

This paper concerns scheduling policies in a surveillance system aimed at detecting a terrorist attack in time. Terrorist suspects arriving at a public area are subject to continuous monitoring, while a surveillance team takes their biometric signatures and compare them with records stored in a terrorist database. Because the surveillance team can screen only one terrorist suspect at a time, the team faces a dynamic scheduling problem among the suspects. We build a M/G/1 queue with two types of customers-red and white-to study this problem. Both types of customers are impatient, but the reneging time distributions are different. The server only receives reward by serving a red customer, and can use the time a customer has spent in the queue to deduce its likely type. In a few special cases, a simple service rule-such as the first-come-first-serve rule-is optimal. We explain why the problem is in general diffcult, and develop a heuristic policy motivated by the fact that terrorist attacks are rare events.the epidemic. Some policy recommendations are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Jun 27, 2008
Accession Number
ADA487113

Entities

People

  • Kyle Y. Lin
  • Moshe Kress
  • Roberto Szechtman

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Databases
  • Distribution Functions
  • Homeland Security
  • Markov Chains
  • Mathematical Models
  • Models
  • Monte Carlo Method
  • Operations Research
  • Probabilistic Models
  • Probability
  • Random Variables
  • Scheduling (Production)
  • Security
  • Simulations
  • Steady State
  • Surveillance
  • Terrorists

Readers

  • Mathematical Modeling and Probability Theory.
  • Operations Research
  • Political Violence and Terrorism Studies.