Scheduling deep-space network data transmissions: a Lagrangian relaxation approach

Colin E. Bell

doi:10.1117/12.141750

23 March 1993 Scheduling deep-space network data transmissions: a Lagrangian relaxation approach

Colin E. Bell

Proceedings Volume 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry; (1993) https://doi.org/10.1117/12.141750
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

For various projects (satellites) one must schedule transmissions to receiving antennas on earth for a one week planning horizon. Periods of time in which any satellite is `in view' of any antenna are known in advance. The scheduling problem is formulated as an integer linear program. This formulation includes a large number of non-conflict constraints stating that an antenna must not receive data from two or more satellites simultaneously. There are also a smaller number of service level constraints specif)ed by project managers to assure appropriate levels of service. For example, service level constraints might specify for a particular project: a maximum allowable gap between the end of one transmission and the start of the next, a minimum total number of minutes of transmission during a week, a minimum number of transmissions on any day, etc. Lagrangian Relaxation allows service level constraints to be relaxed (temporarily ignored). These constraints are replaced by economic penalties for not satisfying them. The resulting modified scheduling problem is easily solved. The paper concentrates on formulation, solution by Lagrangian Relaxation, and performance on an example using real data for a week in 1996.

Citation Download Citation

Colin E. Bell "Scheduling deep-space network data transmissions: a Lagrangian relaxation approach", Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); https://doi.org/10.1117/12.141750

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available