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In the rapidly evolving Internet of Things (IoT) ecosystem, parallel and distributed computing plays a critical role in managing the massive data flows generated by IoT devices. This includes addressing issues that create implementation challenges, such as processing bottlenecks due to large data volumes and the diversity of IoT devices. To solve these problems, advanced technologies such as MapReduce, parallel databases, and platforms such as Apache Hadoop and Spark are used. These methodologies distribute computing tasks across nodes, speeding up data processing and analysis. Parallel and distributed computing enable organizations to efficiently process IoT data to drive real-time insights and improve service delivery through optimized processing and analysis.

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An Efficient Healthcare Monitoring System Using IoT

  • 章节

  • 发表日期：

    2025年

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  • G. Komarasamy,
  • R. Ganeshan,
  • Ahmed Abdou,
  • Maram Y. Al-Safarini,
  • Mohammad Kouali

摘要

In the rapidly evolving Internet of Things (IoT) ecosystem, parallel and distributed computing plays a critical role in managing the massive data flows generated by IoT devices. This includes addressing issues that create implementation challenges, such as processing bottlenecks due to large data volumes and the diversity of IoT devices. To solve these problems, advanced technologies such as MapReduce, parallel databases, and platforms such as Apache Hadoop and Spark are used. These methodologies distribute computing tasks across nodes, speeding up data processing and analysis. Parallel and distributed computing enable organizations to efficiently process IoT data to drive real-time insights and improve service delivery through optimized processing and analysis.