A Cloud-based Analytics-Platform for User-centric Internet of Things Domains – Prototype and Performance Evaluation

Abstract

Data analytics have the potential to increase the value of data emitted from smart devices in usercentric Internet of Things environments, such as smart home, drastically. In order to allow businesses and end-consumers alike to tap into this potential, appropriate analytics architectures must be present. Current solutions in this field do not tackle all of the diverse challenges and requirements, which were identified in previous research. Specifically, personalized, extensible analytics solutions, which still offer the means to address big data problems are scarce. In this paper, we therefore present an architectural solution, which was specifically designed to address the named challenges. Furthermore, we offer insights into the prototypical implementation of the proposed concept as well as an evaluation of its performance against traditional big data architectures.

Reinforcement learning multi-agent system for faults diagnosis of mircoservices in industrial settings

“…The approach used a support vector machine and a convolution neural network in each node. Theo et al [17] present an end-to-end solution for data analytic in microservice architectures. It addressed important requirements and challenges of analytic of microservices, with illustration on smart homes [18].…”

Big Data Systems

“…As a real case study, Zschörnig et al [2020] propose an analytics platform architecture based on the concepts of Kappa and microservices, to predict electricity consumption of households over a period. Smart meters produce consumption data, while various types of meters are used by various households.…”