Towards Sustainable Satellite Edge Computing

TL;DR

This paper proposes an online energy scheduling algorithm for satellite edge computing that minimizes battery discharge, extending satellite operational life despite wireless and energy harvesting uncertainties.

Contribution

It introduces a novel online convex optimization-based algorithm to optimize energy usage in satellite edge computing, addressing battery longevity issues.

Findings

Significantly reduces battery discharge depth

Achieves sub-linear regret in energy scheduling

Constraints are asymptotically satisfied

Abstract

Recently, Low Earth Orbit (LEO) satellites experience rapid development and satellite edge computing emerges to address the limitation of bent-pipe architecture in existing satellite systems. Introducing energy-consuming computing components in satellite edge computing increases the depth of battery discharge. This will shorten batteries' life and influences the satellites' operation in orbit. In this paper, we aim to extend batteries' life by minimizing the depth of discharge for Earth observation missions. Facing the challenges of wireless uncertainty and energy harvesting dynamics, our work develops an online energy scheduling algorithm within an online convex optimization framework. Our algorithm achieves sub-linear regret and the constraint violation asymptotically approaches zero. Simulation results show that our algorithm can reduce the depth of discharge significantly.