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Publish/Subscribe Method for Real-Time Data Processing in Massive IoT Leveraging Blockchain for Secured Storage.

Mohammadhossein Ataei1, Ali Eghmazi1, Ali Shakerian1

  • 1Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada.

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Summary

This study introduces a scalable platform for Massive Internet of Things (MIoT) data management, achieving low latency and high transaction throughput using Apache Druid, Kafka, and blockchain security.

Keywords:
Apache DruidApache KafkaHyperledger FabricMassive Internet of Things (MIoT)latencypublish/subscribe methodologyreal-time data processingstorage security

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Area of Science:

  • Computer Science
  • Data Engineering
  • Network Systems

Background:

  • The proliferation of Machine-Type Devices (MTDs) in the Internet of Things (IoT) era has led to Massive IoT (MIoT) environments.
  • Managing massive, heterogeneous data streams in real-time poses significant storage and analytical challenges.

Purpose of the Study:

  • To develop and evaluate a robust platform for real-time processing and secure storage of MIoT data streams.
  • To demonstrate low latency and high security for a large number of connected devices.

Main Methods:

  • Utilized Apache Druid (v28.0.0) for real-time analytical processing of data streams.
  • Implemented a publish/subscribe mechanism with Apache Kafka (v3.6.1) for efficient data ingestion and broker communication.
  • Incorporated dual Software-Defined Radios (SDRs) for connectivity redundancy and Hyperledger Fabric for secure, immutable data storage.

Main Results:

  • Achieved data transmission latency below 25 milliseconds for 100,000 MIoT devices.
  • Demonstrated high-performance blockchain security with over 800 Transactions Per Second for 14,000 transactions.

Conclusions:

  • The proposed platform effectively addresses the challenges of MIoT data management by providing low latency and enhanced security.
  • The integration of advanced technologies like Kafka, Druid, and blockchain ensures a scalable and reliable solution for real-time data processing.