Abstract

We investigate the fault diagnosis problem for all- optical networks with probabilistic link and node failures in this paper. Our major contribution is the development of diagnosis algorithms that minimize the operating effort to identify failures. We achieve this by employing the fault diagnosis approach based on proactive probing with perfect feedback: knowledge of the network state is progressively refined through a sequence of optical probe signals, each of which is determined upon the results of previous probe signals (i.e. probe syndromes). To detect and localize failures in all-optical networks with probabilistic node and link failures, we introduce a network transformation that maps both link and node failures in an undirected graph into arc failures in a directed graph and apply our previously developed run-length probing scheme [1] to the directed graph. Our analytical and numerical investigation verifies our previously established guideline for efficient fault diagnosis algorithms: each probe should provide approximately 1-bit of state information, and thus the total number of probes required is approximately equal to the entropy of the network state. Hence the complexity of optical network fault management functionality is fundamentally related to the information entropy of the network state.

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