Task scheduling for optimal power management and quality-of-service assurance in CubeSats

Abstract The value and overall efficacy of a satellite mission are directly affected by its task scheduling strategy and the associated amount of work performed in orbit. Despite subject to many constraints, task scheduling is ultimately restricted by the amount of power available at any given moment. In this paper, we propose a mathematical integer programming (IP) formulation designed to maximize the number of tasks to be executed by a satellite, constrained to the amount of power available at any moment along the course of an orbit. The optimization model is formulated to contemplate task priority, minimum and maximum number of task activation, minimum and maximum execution time, minimum and maximum period of a given task and execution window. The variant power input vector was calculated based on the solar cells efficiency, and also on an analytical model used to estimate the irradiance field according to parameters of orbit and attitude. To demonstrate the applicability of our methodology, we conduct several experiments considering three satellite sizes with different orbits and task parameters. The results show that the proposed offline scheduling algorithm generates an optimal energy effective scheduling plan, allowing the best possible use of available energy resources while ensuring the quality of service (QoS).