Jul 2026· International Mediterranean Conference on Communications and Networking· pp. 1-6· 0 citations· 12 references
Computer Science
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.
This work introduces a HAP-native Agentic AI framework and identifies trustworthy control, collaborative multi-HAP orchestration, and digital-twin-assisted lifelong adaptation as key steps toward deployable, sustainable, and resilient SAGIN intelligence.
Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency requests may arrive after committed routine-plan execution has begun. The resulting dynamic emergency observation scheduling problem (DEOSP) requires urgent tasks to be inserted under intermittent ground contact without excessive routine-plan disruption. To address DEOSP, we propose a task-driven three-layer distributed scheduling (T3L-DS) method, which represents task demand and sensor footprints on a common geographic grid and forms temporary clusters from observation capabilities and current inter-satellite links. For intra-cluster coordination, T3L-DS introduces onboard dual-plan bidding and joint marginal evaluation. It also designs an inter-cluster coordination mechanism for unresolved demand. Extensive computational experiments compare T3L-DS with centralised simulated annealing (SA), an adapted selective time-variant better reply process (A-SeTVBRP), and a conventional contract-net protocol (CNP). T3L-DS achieves the highest emergency coverage among the distributed methods, with average relative improvements of approximately 2.8% and 17.1% over A-SeTVBRP and CNP, respectively. Its average relative gap from SA is approximately 7.1%. Under conflict-enhanced loads, it reduces routine-coverage loss by approximately 57.9% and 87.7% relative to A-SeTVBRP and CNP, respectively. The ablation study confirms the contribution of the proposed coordination enhancements. Overall, the results show that T3L-DS provides an effective distributed approach to DEOSP.
The demand for Low-earth-orbit (LEO) satellite networking and routing is continuously growing. Container-based satellite network emulation becomes an important networking evaluation choice for LEO satellite network. While many container-based satellite network emulators optimize virtual network efficiency, they often overlook route installation latency—the duration of installing computed routes into kernel routing table. This latency represents a significant bottleneck for emulating large-scale LEO constellations, which are characterized by dynamic topologies and frequent, massive routing re-convergences. High routing installation latency not only reduces emulation efficiency but also compromises evaluation reliability and renders subsequent data transmission experiments infeasible. In this paper, we present a Lock-Free and Filtered Route Installation (LFRI) mechanism. LFRI filters out non-effective route installations, thereby shortening the installation procedure without changing the routing results. LFRI employs a lock-free installation mechanism that enables parallelized and efficient route installation. Experimental results demonstrate that, compared to the legacy Netlink installation, LFRI reduces the route installation latency by up to 99.9% in emulations of typical LEO satellite constellations, bringing it down to under ten milliseconds, within a performance level comparable to routing installation on physical machines. Meanwhile, in the case study evaluating path availability ratio and restoration time, LFRI yields more consistent and credible experimental data.
Wenhao Lu, Zhiyuan Wang, Shan Zhang et al.· Asia-Pacific Workshop on Net...· 0 citations
COSME is presented, a route-aware, real-time mobility emulator that integrates multiple impairment models - including obstruction-based loss, constellation-induced jitter, precipitation-driven bandwidth reduction, and packet loss at handovers - into a single framework by orchestrating Linux network namespaces via tc and netem.
Eric Lanfer, Dominic Laniewski, Till Zimmermann et al.· Conference on Applications,...· 0 citations
A systems vision for AI infrastructure in space is developed as the systems layer that manages AI capabilities across spacecraft, orbital networks, ground stations, and cloud backends, while treating orbital and physical state as part of the resource model.
Qing Li, Qiyang Zhang, Daliang Xu et al.· 0 citations
This work introduces KAT-MAPPO, a Kolmogorov–Arnold Transformer-enhanced Multi-Agent Proximal Policy Optimization scheme that significantly outperforms existing baselines and highlights the promise of reinforcement learning considering temporal dynamics for efficient offloading in heterogeneous CEG systems.
Chenyang Wang, Qifeng Han· ACM Transactions on Internet...· 0 citations
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