Microservices Architecture for Data Analytics in IoT Applications

Microservices Architecture for Data Analytics in IoT Applications

Arunjyoti Das, Abhijit Bora
Copyright: © 2024 |Pages: 14
DOI: 10.4018/979-8-3693-2260-4.ch011
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Abstract

The internet of things (IoT) is a network of physical objects with sensors, software, and network connectivity built in to enable data collection and sharing. It has led to an exponential increase in data generation, necessitating the development of effective statistical analysis for a range of IoT applications. Predictive analytics is an essential procedure that converts unprocessed data into meaningful insights. To improve decision-making and enhance IoT application performance, it is crucial to create innovative data processing methods and predictive analytical models that can handle the volume and complexity of IoT data. Microservices-based strategies can be implemented to create scalable, reusable, and effective IoT-based analytics solutions.
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2. Background And Related Study

There is limited study available for architecture with IoT and microservices –based architecture with IoT. Hence a comprehensive study on this topic is not yet done. There are a few noted architectural difficulties with the internet of things (Maney et al., 2017; Shahid et al., 2017; Jacob et al., 2018; Oquendo et al., 2017). We have figured out some quality attributes of IoT (Kim, 2016). Other issues with the internet of things have been noted, such as scalability and interoperability. Issues with implementation, competency, security, privacy, data volume, mobility, interoperability, and scalability have all been brought up in relation to IoT (Ninikrishna et al., 2017; Patra et al., 2017; Breivold at al., 2015).

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