A motifs-based Maximum Entropy Markov Model for realtime reliability prediction in System of Systems

摘要

System of Systems (SoS) based on service composition is considered as an effective way to build large-scale complex software systems. It regards the system as a service and integrates multiple component systems into a new system. The performance of the component system may fluctuate at any time because of the complex and changeable running state and external environment of the component system, which will affect the running of the SoS. The online reliability prediction technology is used to predict the reliability of the component system of an SoS in the near future. It aims to find errors and correct them in time so as to ensure that the SoS can run continuously and smoothly. To tackle the reliability prediction problem of component system in a dynamic and uncertain environment, the paper integrates Maximum Entropy Markov Model (MEMM) with time series motifs to achieve a new prediction model (m_MEMM), which is referred to as motifs-based MEMM. Extensive experiments are conducted to demonstrate the effectiveness and accuracy of the proposed approach. (C) 2019 Elsevier Inc. All rights reserved.