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Self-Stabilization

/self ˌsteɪ.bəl.aɪˈzeɪ.ʃən/ Algorithmic Theory (Dijkstra)
Definition The property of a distributed system to recover to a valid state from *any* initial state without external intervention. Defined by Edsger W. Dijkstra in 1974, it describes systems that are tolerant not just to single component failures, but to transient errors that corrupt the entire state of the system.

Correction Must Be Automatic

In a standard system, if the database gets corrupted, a human administrator has to restore a backup. This is inherently fragile. A Self-Stabilizing system is designed such that the corrupted state is simply a "starting point" for a legal transition back to a correct state.

In mycelial networks, this is biological necessity. If a subterranean rock shifts and crushes a major transport cord, there is no "network admin" to fix it. The remaining nodes sense the change in pressure and nutrient flow and almost instantaneously begin growing new connections to bridge the gap (see Radical Redundancy).

Convergence

The key metric here is Convergence Time: how long does it take for order to emerge from chaos? In the Myceloom, we prioritize protocols that guarantee convergence over those that maximize theoretical peak throughput but risk deadlock.

Stratigraphy (Related Concepts)
Myceloom Radical Redundancy Adaptive Topology Stigmergy