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A Time-Driven Cloudlet Placement Strategy for Workflow Applications in Wireless Metropolitan Area Networks.

Jianshan Zhang1,2, Ming Li1,2, Xianghan Zheng1,2

  • 1College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China.

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|May 20, 2022
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Summary

Mobile edge computing (MEC) enhances mobile apps by distributing cloud power to edge servers. This study optimizes cloudlet placement for workflow applications, reducing execution time by up to 44.99%.

Keywords:
cloudlet placementcomputation offloadingmobile edge computingwireless metropolitan area networkworkflow application

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Area of Science:

  • Computer Science
  • Mobile Computing
  • Network Engineering

Background:

  • Mobile devices face increasing computational demands, exceeding their capabilities.
  • Mobile Edge Computing (MEC) distributes cloud resources to network edges, improving performance.
  • Existing research on cloudlets often overlooks placement impact and data dependencies.

Purpose of the Study:

  • To address the cloudlet placement problem for workflow applications (WAs) in wireless metropolitan area networks (WMANs).
  • To develop an optimized cloudlet placement strategy considering task dependencies and network conditions.

Main Methods:

  • A novel cloudlet placement strategy, PGEL (Particle Swarm Optimization with Genetic Algorithm Operators and Encoding Library Updating), was devised.
  • The PGEL algorithm optimizes cloudlet placement for improved computational offloading.
  • Workflow applications (WAs) were used to simulate and evaluate the proposed strategy.

Main Results:

  • The PGEL strategy achieved near-optimal cloudlet placement schemes.
  • The proposed method significantly reduced the execution time of WAs.
  • Compared to classic algorithms, execution time was reduced by 15.04-44.99%.

Conclusions:

  • Optimized cloudlet placement is crucial for efficient mobile edge computing.
  • The PGEL strategy offers a superior approach to cloudlet placement for WAs.
  • This research contributes to enhancing MEC performance in wireless metropolitan networks.