ETaSCoN - Energy-aware Task Scheduling for quality-of-service assurance in Constellations of Nanosatellites

ETaSCoN is a Julia package dedicated to energy-aware task scheduling for quality-of-service assurance in constellations of nanosatellites

Dependencies

• Julia
• JuMP
• Gurobi

Usage

# Instantiating the Mavrotas
result = mavrotas("input_file")

Data file

Where input_file is a julia lang file (.jl) containing the following definitions:

variable	definition
restringe
d	accepted SoC variation within an orbit
M	a large number which would not be part of any optimal solution, used in big-M constraints
LimiteTempo	maximum solving time
LimiteGap	maximum solving gap
q	nominal battery capacity (in Ah)
soc_inicial	initial battery SoC
rho	minimum accepted battery SoC
bat_usage	maximum charge/discharge battery current (in Ampères)
ef	battery charge/discharge efficiency
v_bat	battery voltage
subs	number of subsystems
jobs	number of jobs
T	time horizon
constelação	vector indicating, for each task, weather they are individual (0) or collective (1)
sincronous	vector indicating, for each task, weather they are synchronous (1) or not (0)
min_statup_g	vector containing the minimum number of startups for each job globally (i.e., all satellites)
max_statup_g	vector containing the maximum number of startups for each job globally (i.e., all satellites)
min_cpu_time	vector containing the minimum cpu time for each job for each satellite
max_cpu_time	vector containing the maximum cpu time for each job for each satellite
min_periodo_job	vector containing the minimum period for each job for each satellite
max_periodo_job	vector containing the maximum period for each job for each satellite
min_statup	vector containing the minimum number of startups for each job for each satellite
max_statup	vector containing the maximum number of startups for each job for each satellite
priority	vector containing the priority of each job for each satellite
win_min	minimum time window for each job for each satellite
win_max	maximum time window for each job for each satellite
uso_p	vector containing the power usage of each job
recurso_p	vector containing the available resource for each time instant

Output files

Three output files are generated, namely:

• $(input_file)_Bmax_EN.txt
  • Data format: sub,t,recurso_tot,recurso_A,recurso_B,solar,soc
• $(input_file)_Bmax_SCH.txt
  • Data format: sub,job,x[1],..,x[T]
• $(input_file)_Amax_EN.txt
  • Data format: sub,t,recurso_tot,recurso_A,recurso_B,solar,soc
• $(input_file)_Amax_SCH.txt
  • Data format: sub,job,x[1],..,x[T]
• $(input_file)_mavrotas.txt
  • Data format: A,B

References

Library inspired by Cezar Augusto Rigo`s task scheduling papers.

1. Rigo, C. A.; Seman, L. O.; Camponogara, E.; Morsch Filho, E.; Bezerra; E. A . . Task scheduling for optimal power management and quality-of-service assurance in CubeSats. ACTA Astronautica, v. 179, p. 550-560, 2021.

2. Rigo, C. A. ; Seman, L. O. ; Camponogara, E. ; Morsch Filho, E. ; Bezerra, E. A. . A nanosatellite task scheduling framework to improve mission value using fuzzy constraints. EXPERT SYSTEMS WITH APPLICATIONS, v. 175, p. 114784, 2021.

3. Rigo, C. A. ; Seman, L. O. ; Camponogara, E. ; Morsch Filho, E. ; Bezerra, E. A. ; Munari Junior, P. A. . A branch-and-price algorithm for nanosatellite task scheduling to improve mission quality-of-service. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022.