ARMS: An Analysis Framework for Mixed Criticality Systems

Abstract

The current era of ubiquitous computing and infor-mation overload prompts for a collaborative knowledge manage-ment and decision support system to pursue genuine scientific re-search. Diverse results by various research groups in the real-time mixed criticality community mandates an online decision support system to disseminate information. The prevalence of real-time mixed criticality systems in a large number of application domains has given birth to several task models in literature. Rigid certification requirements and accurate schedulability analysis in the mixed criticality domain require appropriate and well-defined task models, tools and techniques. This paper presents our efforts in the design and development of a knowledge management and decision support system ARMS - a cloud-based analysis tool for mixed criticality systems. ARMS is a unique and novel platform that brings synthesized knowledge on contemporary research in mixed criticality systems together and provides a platform to collaborate with like-minded academicians and engineers. The harmonized research results disseminated by ARMS serves both as an exploratory platform as well as a decision support system for assisting industrial deployment. ARMS is hosted on Amazon Amplify and the user interface is implemented using ReactJS. ARMS serves as a ready-made analyzer for researchers to validate their designs and acts as a quintessential reference aid for academicians and engineers in the mixed criticality domain.