Automated Scheduling for NASA's Deep Space Network

Authors

  • Mark D. Johnston Jet Propulsion Laboratory, California Institute of Technology
  • Daniel Tran Jet Propulsion Laboratory, California Institute of Technology
  • Belinda Arroyo Jet Propulsion Laboratory, California Institute of Technology
  • Sugi Sorensen Jet Propulsion Laboratory, California Institute of Technology
  • Peter Tay Jet Propulsion Laboratory, California Institute of Technology
  • Butch Carruth Innovative Productivity Solutions, Inc.
  • Adam Coffman Innovative Productivity Solutions, Inc.
  • Mike Wallace Innovative Productivity Solutions, Inc.

DOI:

https://doi.org/10.1609/aimag.v35i4.2552

Abstract

This article describes the DSN scheduling wngine (DSE) component of a new scheduling system being deployed for NASA's deep space network. The DSE provides core automation functionality for scheduling the network, including the interpretation of scheduling requirements expressed by users, their elaboration into tracking passes, and the resolution of conflicts and constraint violations. The DSE incorporates both systematic search and repair-based algorithms, used for different phases and purposes in the overall system. It has been integrated with a web application which provides DSE functionality to all DSN users through a standard web browser, as part of a peer-to-peer schedule negotiation process for the entire network. The system has been deployed operationally and is in routine use, and is in the process of being extended to support long-range planning and forecasting, and near-real-time scheduling.

Downloads

Published

2014-12-22

How to Cite

Johnston, M. D., Tran, D., Arroyo, B., Sorensen, S., Tay, P., Carruth, B., Coffman, A., & Wallace, M. (2014). Automated Scheduling for NASA’s Deep Space Network. AI Magazine, 35(4), 7-25. https://doi.org/10.1609/aimag.v35i4.2552

Issue

Section

Articles