本文へ移動
AI NEWS JOURNAL
arXiv cs.DCAI NEWS / JOURNAL

定常状態実行プリミティブとしての移行:低軌道における仮想的静止性のためのランタイム

arXiv:2610.32720v1 発表タイプ:新規 要旨:低軌道(LEO)衛星によるメガコンステレーションは、遅延が極めて重要な地球中心型アプリケーション向けに軌道上エッジコンピューティングを実現しますが、衛星の運動により視線通信の窓はわずか数分にまで圧縮されます。論理的な地理的近接性を維持するため、仮想静止状態(VS)と呼ばれるパラダイムでは、アプリケーションはコンステレーション内を通過する各衛星間で継続的に移動しなければなりません。従来のライブマイグレーション手法は、個別に開始される移動や複製を最適化するものですが、軌道運動によって必要となる連続的なホスト間の引き継ぎには対応していません。そこで私たちは、ライブマイグレーションを定常状態の実行モデルとして再定式化し、新たな仮想静止状態ランタイムパラダイムを提案します。さらに、連続的な移行の実現可能性を形式的に定式化し…

翻訳待ちです。完了すると自動更新されます。

Abstract:Low Earth Orbit (LEO) satellite mega-constellations enable orbital edge computing for latency-critical geocentric applications, but satellite motion compresses line-of-sight communication windows to mere minutes. To maintain logical geographic proximity, a paradigm termed Virtual Stationarity (VS), applications must continuously migrate across passing satellites in the constellation. Traditional live migration mechanisms optimize individually initiated relocations or replication, but not the continuous handover between successive hosts that orbital motion requires. We reformulate live migration as a steady-state execution model and introduce a novel virtual stationarity runtime paradigm. We formalize the viability of continuous migration through a lightweight model capturing latency and availability service-level objectives (SLOs), continuous migration overhead, and the convergence bound of state replay. To satisfy these constraints, we derive a Virtual Stationarity Runtime (VSR) framework whose Migration Membrane combines Capability Virtualization and Continuous State Projection to rebind host resources and reconstruct evolving execution on a successor. Evaluation on physical heterogeneous hosts shows 95th-percentile downtime below 6 milliseconds across 300 recurrent handovers, migration time effectively invariant to memory-write rate, and no cumulative growth in migration time or continuation state. A 1,600-satellite simulation further confirms completion within orbital handover windows.

Submission history

Access Paper:

View PDF

HTML (experimental)

TeX Source

Additional Features

Audio Summary

Current browse context:

References & Citations

Google Scholar

Semantic Scholar

Bookmark

Institution

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

情報源

arXiv cs.DC
← すべてのニュースへ