1. The Deep Space Network Scheduling Problem Brad Clement, Mark Johnston Artificial Intelligence Group Jet Propulsion Laboratory California Institute of Technology {bclement, mdj}@aig.jpl.nasa.gov http://ai.jpl.nasa.gov/ Brad Clement, Mark Johnston Artificial Intelligence Group Jet Propulsion Laboratory California Institute of Technology {bclement, mdj}@aig.jpl.nasa.gov http://ai.jpl.nasa.gov/

2. Space Networks

3. Deep Space Network (DSN)

4. Activities, Tracks, & Viewperiods A track is an allocation of an antenna to a mission over some time interval A viewperiod is the time interval when a spacecraft is visible to an antenna An activity is a track wrapped with setup and teardown time

5. Deep Space Network Scheduling 56 missions 12 antennas –different capabilities –shared equipment –geometric constraints –human operator constraints some schedule as long as 10 years into future ~370 tracks & ~1650 viewperiods per week ~2000 tracks & ~80000 viewperiods per year some require schedule freeze 6 months out complicated requirements originally from agreement with NASA with flexibility in antennas, timing, numbers of tracks, gaps, etc. ~30 people employed full time to schedule for multiple missions schedule centrally generated, meetings and horse trading to resolve conflicts similar to coordination operations across missions

6. Other Space Scheduling Problems comm. scheduling TDRSS and AFSCN Mars relay scheduling antenna command generation science planning measurement scheduling command sequence generation (ground and onboard)

7. Constraints No two spacecraft can use antenna at same time –except MSPA where antenna points to both (2 at most) and uplinks to at most one Spacecraft must be in view of antenna At Goldstone, no track/activity can be scheduled where two other tracks/activities start within 15 minutes –except the four Cluster s/c At other complexes, no two may start within 5 minutes of each other U/L D/L U/L D/L MEX MERA NAV 0 5 2322 32 30

8. Scheduling Requirements Under Constraints B. Clement, S. Schaffer Implemented algorithm for automating scheduling of requirements: optional antennas (DSS14, 15, or 24) BOT and duration ranges periodic tracks locks on BOT, duration, and antenna MSPA arraying / VLBI / delta DOR continuous tracks segmentation gap-to-track ratio DSS-15 DSS-45 DSS-65 DSS-25 DSS-65 DSS-66 DSS-15DSS-45DSS-65 DSS-25 MEX MGSODY

9. Requirements –abstraction of requirements as an AND/OR tree →use HTN planning –optional and/or multiple resource usage –start time and duration ranges –temporal constraints (STN) –all activity/track start times and durations must be evenly divisible by 5 minutes (except for Cluster) –locks on resource and timing →remove resource choices (OR branches) →add/shrink temporal constraints to current time allocation →ASPEN has scheduling permissions –override / blockout [3hr, 8hr] 0 ∞ 0 ∞

10. Requirements (cont’d) periodic tracks – ranges specified for some of: initial start time overall end of period number of tracks total duration of tracks duration of individual tracks time gap/overlap

11. Scheduling in ASPEN Start (if conflicts exist and user time-limit not exceeded)... Select a conflict Select a repair method... move... Select an activity Select a start time Perform the action, collect the new conflicts, and repeat

12. Scheduling Performance Generates schedule of 1861 tracks from ~3 weeks of requests in 39 minutes (resolving 2305 initial view period/antenna conflicts) Reschedules to accommodate individual emergency tracks in 0.2 seconds and emergency antenna downtime in 0.2 seconds Handles doubling of one mission’s track requests over one week (to 42 total) in 2.7 seconds Initial performance acceptable for interactive conflict resolution, possibly for initial schedule generation

13. Systematic Search Algorithms Local search in ASPEN can handle large schedules (for long-term requirements) but gives no guarantees of optimality or that an existing solution will be found Systematic search can give these guarantees for small problems (conflict resolution) –BT1: depth-first backtracking, all times/resources permitted (provided there are viewperiods available) most constrained first track selection smallest  from original time/antenna assignment –BT2: same as BT1 but limited to original antenna –A*: optimal graph search, objective is to minimize changes from original schedule (in both both antenna and time) –Assumptions made for these algorithms and experiments: track durations are fixed in these experiments tracks that span day boundaries are considered locked in place tracks without viewperiods are considered locked in place

14. M. Johnston Resolving conflicts for Schedule after Conflict Negotiation Meeting Finds solution (or proves no solution) to each within a few hundredths of a second Found optimal solutions to most within a few minutes

15. M. Johnston Finds solution to each within a few hundredths of a second Found optimal solutions to most within a few minutes Resolving conflicts Schedule Before Conflict Negotiation Meeting

16. User-Interface Design Met repeatedly with users (MDAPT, RAPSO, DSN, and mission operations staff) to understand requirements and obtain feedback on application design. Collaboration with NASA Ames’ Human Computer Interaction group (Alonzo Vera, Mike McCurdy & Chris Connors), who (with us and user feedback) have designed user-interfaces. –designed interface for editing of requirements –designed interface for refining requirements with aid of automated scheduler

17. Requirements Editor Dialog

18. Visualization Gantt chart design Mouse over details in tabular view simultaneous schedule + metric visibility w/user- specifiable gradient visualization of differences between two schedule versions

19. Applications – DSN Arrays NASA may build 3600 10m weather- sensitive antennas 1200 at each complex in groups of 100 spread over wide area High automation requested—one operator for 100 or 1200 antennas Spacecraft may use any number of antennas for varying QoS, and may need link carried across complexes Only some subsets of antenna signals can be combined –depends on design of wiring/switching to combiners –combiners may be limited Local response time should be minimized