Monitoring at Any Cost

Abstract

Rules are integral to our social and business reality. In many domains, rules are sufficiently precise and straightforward that compliance can be monitored automatically. Abstractly, a monitor takes a rule as an input, expressed in some specification language, and then processes a stream of timestamped events while detecting and outputting violations of the rule as early as possible. In practice, monitors face challenging real-world requirements like handling immense volume of streamed data that arrives at a high velocity. State-of-the-art monitors struggle to meet this requirement.We shall study and develop monitors that scale in real-world settings by learning and exploitinginformation about the event stream and by explicitly trading off output details and precision in order to optimize the monitors’ operation. We outline three monitoring approaches, ordered with respect to their ability to handle increasing volume and velocity of streams of events. We will develop parallel monitors that efficiently utilize available resources, as well as monitors that can improve their efficiency by omitting details from their output when necessary. Finally, if all else fails, we will allow the monitors to be incorrect with a very low probability, while still providing useful information in real time.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 11, 2017
Source ID
FA95501710306

Entities

People

  • David Basin

Organizations

  • Air Force Office of Scientific Research
  • ETH Zurich
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Distributed Systems and Data Platform Development
  • Human-Computer Interaction (HCI).