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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Task arrival based energy efficient optimization in smart-IoT data center.

Bin Wang1, Fagui Liu1

  • 1School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China.

Mathematical Biosciences and Engineering : MBE
|April 24, 2021
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Summary
This summary is machine-generated.

This study introduces a new method for managing cloud data center energy consumption, specifically for Internet of Things (IoT) workloads. The proposed energy-efficient scheduling algorithm optimizes resource allocation for smart cities.

Keywords:
VM placementenergy efficiencygreen data centerssmart citiestask arrival

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Area of Science:

  • Cloud Computing
  • Smart Cities
  • Energy Efficiency

Background:

  • Cloud data centers face increasing energy demands, impacting smart city sustainability.
  • Existing resource management methods neglect the unique characteristics of Internet of Things (IoT) device workloads.

Purpose of the Study:

  • To address energy consumption in cloud data centers for smart cities.
  • To develop a resource management approach tailored for IoT workloads.
  • To optimize energy efficiency while maintaining service level agreements.

Main Methods:

  • Analysis of IoT request characteristics.
  • Development of an improved Poisson task model for predicting IoT request arrivals.
  • Introduction of an adaptive energy efficiency model for balancing energy saving and service levels.
  • Proposal of an energy-efficient virtual machine scheduling algorithm.

Main Results:

  • The proposed method effectively predicts IoT request arrivals.
  • The adaptive model successfully balances energy saving with service level agreements.
  • The energy-efficient virtual machine scheduling algorithm maximizes data center energy efficiency.
  • Experimental results demonstrate superior performance compared to existing schemes.

Conclusions:

  • The developed approach enhances energy efficiency in cloud data centers for smart cities.
  • The novel scheduling algorithm is effective for managing IoT workloads.
  • This work contributes to sustainable smart city development through optimized cloud resource management.