Meteornet: Continuous-Time Emulation Platform for Edge Intelligence in Leo Constellations

Abstract

Mega-constellations of Low Earth Orbit (LEO) satellites are enabling a new Space Cloud paradigm in which edge servers hosted on-board process tasks autonomously, reducing ground-segment latency for globally dispersed users. Realizing this vision requires Collaborative Edge Intelligence (CEI): distributed algorithms that coordinate Multi-access Edge Computing (MEC) server activation, task offloading, and routing across a time-varying orbital topology. Existing evaluation tools are inadequate—simulation platforms abstract away protocollevel behavior, while emulation testbeds lack orbital dynamics. This paper presents MeteorNet, an open-source, continuous-time emulation platform that integrates SGP4 orbital propagation, Mininet/ONOS network emulation, Docker-containerized MEC services, and MongoDB telemetry. Supporting eight orchestration strategies, including Fuzzy Logic and distributed Reinforcement Learning controllers, MeteorNet enables apples-to-apples CEI benchmarking under realistic orbital conditions. Experiments show that intelligent controllers halve the MEC activation cost at low load, while revealing an orbital-visibility bottleneck that limits task success at high load, regardless of the orchestration policy.