A general algorithm for detecting faults under the comparison diagnosis model

Abstract

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractWe develop a widely applicable algorithm to solve the fault diagnosis problem in certain distributed-memory multiprocessor systems in which there are a limited number of faulty processors. In particular, we prove that if the underlying graph G = (V, E) forming the interconnection network has connectivity no less than its diagnosability δ and can be partitioned into enough connected components of large enough size then given a syndrome of test results under the comparison diagnosis model resulting from some set of faulty nodes of size at most δ, we can find the actual set of faulty nodes with time complexity O(∆N ), where ∆ is the maximal degree of any node of the graph and N is the number of nodes.

Towards Internet-Scale Convolutional Root-Cause Analysis with DIAGNET

“…Numerous works have been performed in enterprise networks and datacenters, where the full network topology is known (e.g. Clos-like topologies or SDN-driven networks [16], [17], [36]). This topology information allows network tomography techniques to be applied [11]- [15], [37], [38], pinpointing faulty links or components accurately at scale despite complex dependencies between components [39].…”