Definition and implementation of an error injection tool for smart city applications

• Grant number: 22/08421-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): September 01, 2022
• Effective date (End): August 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Fabiano Cutigi Ferrari
• Grantee: Ruan Crysthian Lima Ferraz
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Characteristics of Smart City applications such as diversity of applications, users, types of sensors, and types of produced data are sources of faults and consequential errors that may be generated. This undergraduate research project aims to develop an error injection tool to be applied to Smart City applications, with a focus on the urban mobility and traffic control domains. The tool shall be capable of injecting errors that are typical of these applications. We emphasize that error injection happens at runtime and consists in an activity that is useful for the assessment of fault tolerance strategies that are implemented in software, with a focus on the detection, confinement, evaluation, and recovery of errors. In particular, the research herein proposed composes a research project supported by FAPESP (process N. 2019/25307-8), which primarily aims to devise a fault tolerance approach for Smart City applications. The aimed tool will be designed to be further integrated with a simulation environment of Smart City applications, as a way to make it feasible for the assessment of the fault tolerance approach that will result from the aforementioned research project. We highlight that existing error injection tools will be analyzed from the perspective of reusing their requirements and implementation, with proper customizations for Smart City applications. Furthermore, we highlight that, overall, tools developed in the academic context are fundamental to enabling the academia-industry technology transfer. (AU)