Machine learning based distributed big data analysis framework for next generation web in IoT

For the advancement of the Internet of Things (IoT) and Next Generation Web, various applications have emerged to process structured or unstructured data. Latency, accuracy, load balancing, centralization, and others are issues on the cloud layer of transferring the IoT data. Machine learning is an emerging technology for big data analytics in IoT applications. Traditional data analyzing and processing techniques have several limitations, such as centralization and load managing in a massive amount of data. This paper introduces a Machine Learning Based Distributed Big Data Analysis Framework for Next Generation Web in IoT. We are utilizing feature extraction and data scaling at the edge layer paradigm for processing the data. Extreme Learning Machine (ELM) is adopting in the cloud layer for classification and big data analysis in IoT. The experimental evaluation demonstrates that the proposed distributed framework has a more reliable performance than the traditional framework.

• Publication year

  2021

• Venue

  Computer Science and Information Systems

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.2298/CSIS200330012S
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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