Resilience analysis on self-healing systems

• Grant number: 17/21941-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2018
• End date: January 31, 2019
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Carlos Dias Maciel
• Grantee: Rafael Rodrigues Mendes Ribeiro
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment, AP.TEM

Abstract

The study of system resilience is of great importance today. Within this study, it is highlighted the use of complex network models to analyze the resilience of real systems. In this project, we intend to use this representation to make the resilience analysis of self-healing systems. These systems have the ability to change their topology to recover themselves from a failure. In this work, we will analyze the effect of system redundancy on the resilience and how the system topology affects the resilience of self-healing systems. An algorithm that simulates the reconfiguration of the system in case of failures will be implemented. The four topologies that will be studied are: planar grids, small-world, scale-free and a real system. The analyzes will be performed for a variable number of failures, with faults in edges, nodes or both. The resilience investigation will be done using the fraction of nodes connected to the system after the system reconfiguration over the total number of nodes in the system. With this data it will be possible to infer favorable or unfavorable characteristics for self-healing systems. (AU)