Direct-to-cell satellites enable global network services for our regular phones/IoTs via 4G, 5G, and beyond. To enforce highly available, trustworthy, and roaming policy-compliant network services, they heavily rely on user geolocation and timing information from external global navigation satellite systems (GNSS) to assist with their radio access, authentication, and authorization. Our analysis and field tests reveal that, this cross-technology over-reliance propagates satellite navigation's defects to direct-to-cell satellite networks, leading to diverse issues such as intermittent connectivity, over/under-billing, unauthorized services, and service denials even when direct-to-cell satellites are accessible. Our solution, SN2, adopts the "fate-sharing" principle to reuse direct-to-cell satellites themselves for self-navigating networks. By exploiting the flexible tradeoffs between satellite network availability and navigation accuracy, it enables "good enough" built-in navigation for highly available and functionally correct network services at a negligible cost of hardware or communication resources. Our evaluations with commodity satellite phones and 3GPP NTN protocol stacks demonstrate SN2's 4.4–23.5× network availability boost and 1.9–12.3× access latency reduction over legacy solutions.

Do we really need 10,000s of Low Earth Orbit (LEO) satellites to meet huge global Internet demands? While proven feasible and valuable, such LEO mega-constellation networks have raised concerns about their prohibitive capital expenditures, market monopoly, and unsustainable use of space. Instead, our analysis reveals that most of their satellites can be wasted due to their mismatch with physically uneven demands. We thus propose TinyLEO, a software-defined solution to shrink LEO network size for enormous global demands via dynamic spatiotemporal supply-demand matching. TinyLEO sparsifies satellite supplies on demand by combining diverse yet sparse orbits, hides complexities of this sparse LEO network via orbital model predictive control, and shifts the responsibility for handling these complexities to its geographic segment anycast for higher network usability, lower resource wastes, faster failovers, simpler satellites, and more flexible network orchestration. We have prototyped TinyLEO as a community toolkit for open research. Our evaluation using this toolkit shows that TinyLEO can compress the existing LEO mega-constellation network size by 2.0–7.9×, cut control plane costs by 1–3 orders of magnitude, and maintain the same demands and comparable data plane performance.