Scheduling Policies for an Antiterrorist Surveillance System

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 difficult, and develop a heuristic policy motivated by the fact that terrorist attacks are rare events.