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Design Methodology of Microservices to Support Predictive Analytics for IoT Applications.

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Summary
This summary is machine-generated.

This study introduces a modular microservices design for Internet of Things (IoT) analytics, enabling efficient, scalable, and adaptive support for diverse data and changing requirements in digital transformation. The approach enhances data insights and process productivity.

Keywords:
Internet of Things (IoT)IoT analyticsWeb of Objects (WoO)microservicessemantic ontology

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Area of Science:

  • Computer Science
  • Data Science
  • Software Engineering

Background:

  • The Internet of Things (IoT) is rapidly evolving with advanced data handling capabilities, but faces challenges in integrating heterogeneous data and providing adaptable services.
  • Existing IoT analytic systems struggle with efficiency, maintainability, and scalability due to monolithic architectures and diverse data sources.

Purpose of the Study:

  • To propose a design methodology for an efficient and scalable IoT analytic system.
  • To embed analytic capabilities within modular microservices to support adaptive IoT applications.
  • To address the challenges of heterogeneous data and evolving requirements in IoT environments.

Main Methods:

  • Developed a design methodology integrating analytic capabilities into modular microservices.
  • Created algorithms for analytic procedures to support the proposed model.
  • Utilized Web Objects for IoT resource virtualization and semantic data modeling for interoperability.

Main Results:

  • The proposed design facilitates efficient and scalable services for adaptive IoT applications.
  • Modular microservices enhance the maintainability and adaptability of IoT analytic systems.
  • Semantic data modeling improved interoperability across heterogeneous IoT systems.

Conclusions:

  • The microservices-based approach offers an efficient and scalable solution for IoT analytics.
  • The design methodology effectively addresses the challenges of heterogeneous data and dynamic requirements.
  • The prototype implementation validates the proposed design for adaptive IoT applications.