54 lines
4.1 KiB
Markdown
54 lines
4.1 KiB
Markdown
CosmosMesh MVP
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=============
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CosmosMesh is a privacy-preserving federated mission-planning scaffold designed for deep-space constellations. It targets offline-first operation with intermittent connectivity, enabling heterogeneous assets (rovers, aerial drones, habitat modules, orbiting satellites) to coordinate planning and resource usage without centralization.
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Core ideas
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- Local optimization problems (variables, objectives, constraints) with explicit data contracts and versioning.
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- Federated optimization core: an ADMM-lite solver that exchanges only summarized signals to preserve locality.
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- Lightweight global assembly: fleet-wide constraints (energy, time windows, safety) applied without re-deriving the entire global model.
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- Delta-sync and offline resilience: deterministic reconciliation on reconnects with audit trails.
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- Privacy-by-design: secure aggregation by default, optional local DP budgets, and role-based access controls.
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- Identity & security: DID-based identities, short-lived certificates, and tamper-evident logging.
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- Adapters & simulation: reference adapters for rover/habitat/space assets, plus a scenario simulator for offline validation.
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- Open API and governance: schema registry for data contracts and a governance ledger to anchor decisions.
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MVP plan (8–12 weeks)
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- Implement a 2–3 asset testbed (rover, drone, habitat) with a simple quadratic objective and an ADMM-lite solver.
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- Define data contracts: Telemetry, Forecast, Command, Event, and Trade-like signals with versioned schemas.
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- Delta-sync protocol: deterministic reconciliation for intermittent links with per-message metadata and audit logs.
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- Identity & security baseline: DIDs or short-lived certs, secure aggregation by default.
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- Adapters and simulation: two starter adapters and a space-scenario simulator to evaluate convergence and resilience.
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- Global constraints layer: light fleet-wide constraints that bind local problems during aggregation.
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- MVP milestones: Phase 0 protocol/specs + 2 adapters; Phase 1 offline validation; Phase 2 cross-domain demo; Phase 3 HIL.
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- Metrics: convergence speed, plan-optimality gap, delta-sync latency, and privacy budgets.
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Getting started
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- Build: python3 -m build
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- Test: ./test.sh
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- Explore: src/cosmosmesh_privacy_preserving_federated_/ and src/cosmosmesh_privacy_preserving_federated_/catopt_bridge.py for the MVP scaffolding and the CatOpt bridge (lightweight interoperability layer).
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Notes
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- This repo focuses on a safe, minimal surface suitable for rapid iteration. Extend with adapters for rovers, habitats, and orbital assets, plus a delta-sync protocol and a light global-assembly layer in follow-on work.
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Changelog-style summary
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- Added CatOptBridge (lightweight CosmosMesh -> CatOpt representation) in the MVP scaffold.
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- Exposed CatOptBridge via the MVP package API for quick experimentation.
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- Expanded README to reflect MVP architecture, extension paths, and evaluation plan.
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Public artifacts
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- README.md (detailed MVP plan and extension guidelines)
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- Python modules in src/cosmosmesh_privacy_preserving_federated_ and src/cosmosmesh_privacy_preserving_federated_/catopt_bridge.py
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- Tests in tests/ (smoke test for basic arithmetic)
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- READY_TO_PUBLISH flag to be created when ready for publication
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# CosmosMesh MVP: Privacy-Preserving Federated Mission Planning
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This repository contains a minimal MVP scaffold for privacy-preserving, offline-first, multi-agent mission planning in deep-space fleets. It includes a tiny ADMM-lite solver and contract primitives, plus a CatOpt-style interoperability bridge for cross-domain experimentation.
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Key artifacts:
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- LocalProblem / SharedVariables / DualVariables / PlanDelta / PrivacyBudget / AuditLog contracts (in src/cosmosmesh_privacy_preserving_federated/contracts.py)
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- ADMMLiteSolver (in src/cosmosmesh_privacy_preserving_federated/admm_lite.py)
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- CatOpt bridge (in src/cosmosmesh_privacy_preserving_federated/catopt_bridge.py): minimal translator between CosmosMesh primitives and CatOpt-like representations
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This MVP is designed to be extended in small, well-scoped steps. See AGENTS.md for contribution and testing guidelines.
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