Microservices for Data Analytics in IoT Applications: Current Solutions, Open Challenges, and Future Research Directions

Abstract

The synergy between the Internet of Things (IoT) and big data technologies has resulted in the great development of multiple smart applications in varied fields such as energy management, environmental monitoring, elderly healthcare, etc. Due to the increasing demand for smart applications, opting for a flexible and scalable software architecture that supports and accelerates the development of these applications is in dire need nowadays. As an effective solution to continuously maintain, upgrade, and scale IoT-based applications, the microservices paradigm has been adopted as an architectural style allowing to provide several enhancements in terms of independent deployment, modularity, containerization, loose coupling, etc. These advantages provided by microservices impact also the efficiency of the analytics conducted by the IoT-based systems. In this view, the current research aims to address a survey about the adoption of the microservices paradigm for supporting data analytics in IoT applications. For this purpose, first of all, the theoretical concepts related to IoT, data analytics, and microservices are briefly presented. Second, relevant microservices-based solutions for data analytics in IoT applications are reviewed and discussed. Third, the challenges and opportunities offered by the microservices paradigm in the IoT context are outlined and explained. The present study will pave the way for promising future research on the issues of integrating the emerging microservices technology in data analytics and IoT applications.