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A oneM2M-Based Query Engine for Internet of Things (IoT) Data Streams.

Putu Wiramaswara Widya1, Yoga Yustiawan2, Joonho Kwon3

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This study introduces OMQ, a query engine for the oneM2M standard, enabling efficient real-time processing of Internet of Things (IoT) data streams. OMQ enhances IoT data retrieval and reduces processing time and network bandwidth.

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Area of Science:

  • Computer Science
  • Data Engineering
  • Networking

Background:

  • The oneM2M standard aims to unify Internet of Things (IoT) middleware for interoperability.
  • Existing oneM2M standards lack efficient mechanisms for user-intent-driven IoT data retrieval.
  • Real-time data processing and efficient querying are critical for IoT applications.

Purpose of the Study:

  • To design and develop a oneM2M-based query engine (OMQ) for real-time IoT data stream processing.
  • To enable efficient searching and retrieval of IoT data that aligns with user intentions.
  • To improve the performance of IoT data querying within the oneM2M framework.

Main Methods:

  • Developed a novel query language using JavaScript Object Notation (JSON) for data retrieval.
  • Proposed efficient query processing algorithms leveraging the oneM2M architecture (IoT and infrastructure nodes).
  • Implemented a hybrid infrastructure-edge processing approach for distributed query execution.

Main Results:

  • OMQ facilitates real-time processing of IoT data streams.
  • The system efficiently handles aggregate, transform, filter, and join operators.
  • Experimental evaluations using real and synthetic datasets confirmed OMQ's feasibility and efficiency.
  • Reduced query processing time and network bandwidth consumption were demonstrated.

Conclusions:

  • The OMQ system effectively addresses the limitations of current oneM2M standards for IoT data querying.
  • Hybrid infrastructure-edge processing significantly enhances query execution efficiency in IoT environments.
  • OMQ offers a viable solution for real-time, intent-driven IoT data retrieval and management.