Analysis of Self-Stabilizing Clock Synchronization by Means of Stochastic Petri Nets

Abstract

Consider a distributed system in which the clock synchronization is carried out by a fault-tolerant clock synchronization (FCS) algorithm with the ability to resynchronize periodically all the correct clocking modules in the system. When using this type of mask-based algorithm, the normally required availability of correct clocking modules cannot be maintained unless self-diagnosis and repair functions are added into the system. Once a self-diagnosis scheme is integrated into an FCS design, the problem of controlling and measuring the system's self-stability arises. This paper develops a model for analyzing the FCS system of the type supported by a statistical self-diagnosis. A stochastic Petri net (SPN) model is constructed to derive the self-stability measures of such FCS systems. An example is given to demonstrate the entire modeling and analyzing procedure. The mapping from SPN model to Markov model shown in the example can be automated by using an SPN software package. The results show that the SPN model is an excellent tool in obtaining self-stability measures and that several important system features, such as synchronization and parallelism, can be modeled using the SPN method in a much clearer manner than other available tools. © 1990 IEEE