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Dynamic Power Provisioning System for Fog Computing in IoT Environments

Author

Listed:
  • Mohammed Al Masarweh

    (Department of Management Information System, College of Business in Rabigh, King Abdulaziz University, Jeddah 25732, Saudi Arabia)

  • Tariq Alwada’n

    (School of Computing, Engineering & Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK)

Abstract

Large amounts of data are created from sensors in Internet of Things (IoT) services and applications. These data create a challenge in directing these data to the cloud, which needs extreme network bandwidth. Fog computing appears as a modern solution to overcome these challenges, where it can expand the cloud computing model to the boundary of the network, consequently adding a new class of services and applications with high-speed responses compared to the cloud. Cloud and fog computing propose huge amounts of resources for their clients and devices, especially in IoT environments. However, inactive resources and large number of applications and servers in cloud and fog computing data centers waste a huge amount of electricity. This paper will propose a Dynamic Power Provisioning (DPP) system in fog data centers, which consists of a multi-agent system that manages the power consumption for the fog resources in local data centers. The suggested DPP system will be tested by using the CloudSim and iFogsim tools. The outputs show that employing the DPP system in local fog data centers reduced the power consumption for fog resource providers.

Suggested Citation

  • Mohammed Al Masarweh & Tariq Alwada’n, 2023. "Dynamic Power Provisioning System for Fog Computing in IoT Environments," Mathematics, MDPI, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:116-:d:1309930
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    References listed on IDEAS

    as
    1. Jin, Chaoqiang & Bai, Xuelian & Zhang, Xin & Xu, Xin & Tang, Yu & Zeng, Chao, 2022. "A measurement-based power consumption model of a server by considering inlet air temperature," Energy, Elsevier, vol. 261(PA).
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