Add new scheduler component for distributed ML workload orchestration:
- Hub-based coordination for multi-worker clusters
- Pacing controller for rate limiting job submissions
- Priority queue with preemption support
- Port allocator for dynamic service discovery
- Protocol handlers for worker-scheduler communication
- Service manager with OS-specific implementations
- Connection management and state persistence
- Template system for service deployment
Includes comprehensive test suite:
- Unit tests for all core components
- Integration tests for distributed scenarios
- Benchmark tests for performance validation
- Mock fixtures for isolated testing
Refs: scheduler-architecture.md
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