Mars local computing reduces delays and boosts data from robotic missions
Bandwidth, Latency, and 400 Million Kilometers: The Case for Mars-Local Compute
Distributed, Parallel, and Cluster ComputingNetworking and Internet Architecture
Summary
Sending information from Mars to Earth is very slow and often interrupted, which limits how much data robots can send back. The authors suggest placing computers in Mars orbit to process lots of data locally, then only sending important updates to Earth. This setup would include satellites that stay in fixed positions above Mars, covering most of the planet and helping robots explore more effectively. This could make robotic missions much more productive before we send humans there.
What this means in practice
- •For space mission planners: Design Mars missions that use orbiting computers to process data locally, reducing reliance on slow Earth communication links.
- •For satellite communications engineers: Develop satellite constellations in Mars orbit that provide constant, high-bandwidth links and computing power to surface missions.
A position paper. It proposes an approach and reports no results.
Authors
Maleeha Masood, Indranil Gupta, Deepak Vasisht
Abstract
There have been recent proposals for human settlements on Mars in 2030s. Any human activity on Mars must be preceded by extensive robotic exploration. However, Mars exploration is bottlenecked by the low bandwidth, intermittent Mars-Earth link. For example, HiRISE, a high-resolution camera onboard the Martian orbiter MRO imaged less than 3% of Mars over eleven years, even though MRO's low resolution Context Camera had mapped more than 99% of Mars in that time. We present a systems case for shared compute for Mars exploration. Such Mars-local compute, paired with advances in computer vision and AI, can enable large volumes of data to be collected and processed on Mars while sending periodic updates, insights, and selective datasets to Earth. To overcome the lack of surface infrastructure on Mars, we propose a two-tier in-orbit deployment of computational satellites that provides consistent coverage and bandwidth. Our analysis shows that the proposed deployment can start small: one areostationary node makes compute reachable from all active Mars missions, two additional areostationary nodes can extend this coverage to roughly 90% of the planet, while low-Mars-orbit nodes add high-rate surface links and compute capacity where demand grows.