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Smart city information processing under internet of things and cloud computing.

Peng Su1, Yuanyuan Chen2, Mengmeng Lu1

  • 1Scientific Research Planning Division, Shandong Labor Vocational and Technical College, Jinan, 250022 Shandong China.

The Journal of Supercomputing
|August 9, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a smart city information system using Internet of Things (IoT) and cloud computing. The system demonstrates efficient resource allocation and low latency for enhanced smart city development.

Keywords:
Cloud computingInternet of ThingsSmart citySmart city information systemSmart epidemic prevention

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Area of Science:

  • Computer Science
  • Information Technology
  • Urban Planning

Background:

  • Smart cities generate vast data from diverse sources, creating information silos.
  • Effective data processing and resource management are crucial for smart city functionality.
  • Interconnection and data sharing are key challenges in smart city development.

Purpose of the Study:

  • To explore smart city information (SCI) processing technology using Internet of Things (IoT) and cloud computing.
  • To promote effective sharing and interconnection in smart city construction.
  • To design and verify a SCI system addressing information islands.

Main Methods:

  • Constructed a SCI system integrating smart environment monitoring, transportation, and epidemic prevention.
  • Proposed a multi-objective optimization algorithm for cloud computing virtual machine resource allocation (CC-VMRA method).
  • Analyzed and simulated the application of IoT and cloud computing in the SCI system.

Main Results:

  • The CC-VMRA method significantly reduced physical servers to under 20 with a variance not exceeding 0.0024, ensuring load balancing.
  • IoT gateway packet loss rate using Zigbee protocol was well below 0.1%, with delays under 10 ms.
  • The SCI system achieved low latency and high utilization rates.

Conclusions:

  • The developed SCI system effectively integrates diverse smart city applications.
  • The CC-VMRA method optimizes resource allocation, enhancing efficiency and scalability.
  • The study provides a valuable experimental reference for future smart city infrastructure.