Fault tolerance of recursive match networks based on g-good-neighbor fault pattern

Abstract

The rapid informatization and digitalization of the society heavily rely on the extensive use of parallel and distributed, networked computer systems. It is important for large-scale parallel and distributed systems to be able to detect and tolerate faulty vertices in the network. A network's fault status can often be characterized with the network's connectivity and diagnosability. The connectivity/diagnosability can be defined under various conditions. This paper is concerned with the connectivity/diagnosability under the “g-good-neighbor condition”, which can more accurately measure a network's fault status. In this paper, we propose a new class of recursive networks, named recursive match networks (RMNs), which contain the well-known BCube and BC networks. We determine the RMNs' g-good-neighbor connectivity and g-good-neighbor conditional diagnosability under the classic MM* and PMC diagnostic models for g≥0. Since the RMN is a more general network covering the BCube and BC networks, our results can be directly applied to these two networks.