Analytics of Performance and Data Quality for Mobile Edge Cloud Applications

Abstract

Emerging edge/fog computing models have fostered new types of applications whose software components and dependent services are provisioned across distributed edge and cloud infrastructures. The design of mobile edge cloud systems is complex, thus it is important to understand suitable deployment models and test them. Since mobile edge cloud computing and its deployments are quite new, there is a lack of techniques and knowledge about possible deployments, configurations, and performance evaluation. In this paper, we present our experiences on studying the impact of performance and data quality for mobile edge cloud systems. We use a mobile edge cloud cornering assistance (MECCA) application to examine various performance and data quality impact. In this paper, we explain how by using MECCA to test performance and data quality, we draw key issues and steps in analytics of edge cloud applications and lessons learned for mobile edge computing application testing.