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A Survey on IoT Application Architectures.

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This survey overviews Internet of Things (IoT) application architectures, comparing cloud, edge, and fog computing. It highlights IoT Edge advancements for reduced latency and improved privacy in IoT systems.

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IoT applicationIoT architectureIoT protocolcloudedgefog

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Area of Science:

  • Computer Science
  • Network Engineering
  • Distributed Systems

Background:

  • The Internet of Things (IoT) has rapidly expanded, necessitating optimized application architectures for deployment, operation, and maintenance.
  • Existing IoT architectures face challenges in scalability, latency, and resource efficiency, impacting system performance.

Purpose of the Study:

  • To provide a comprehensive survey of current IoT application architectures.
  • To analyze the strengths, limitations, and deployment models (cloud, edge, fog) of various IoT architectures.
  • To examine emerging trends and solutions from major providers like Intel, AWS, Microsoft Azure, and GCP.

Main Methods:

  • Categorization of IoT architectures based on deployment models: cloud, edge, and fog computing.
  • Comparative analysis of architectural features, focusing on scalability, latency, and resource efficiency.
  • Review of emerging trends and commercial solutions in IoT application management.

Main Results:

  • Cloud architectures offer scalability but suffer from high latency and bandwidth issues.
  • Edge architectures enhance real-time processing and reduce network congestion by moving computation closer to the data source.
  • Fog architectures provide a hybrid approach, balancing cloud and edge capabilities for complex IoT environments.

Conclusions:

  • Latency, privacy, and deployment difficulties are key challenges in current IoT systems.
  • Advancing IoT Edge architectures is crucial for reducing network traffic, enhancing data privacy, and improving interoperability.
  • Development of multi-application and multi-protocol edge gateways is recommended for efficient IoT application management.