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Research on Edge Service Composition Method Based on BAS Algorithm.

Zhoujie Du1, Huaikou Miao1,2

  • 1School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.

Computational Intelligence and Neuroscience
|August 2, 2021
PubMed
Summary

This study introduces an edge computing model for optimized edge service composition using the BAS algorithm. It enhances efficiency and user experience by reducing cloud computation and response times.

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Artificial Intelligence

Background:

  • Edge computing shifts processing from the cloud to network edges, reducing latency and computational load.
  • Effective edge service composition is crucial for maximizing these benefits and improving user experience.
  • Existing methods like PSO and WPA have limitations in optimizing edge service combinations.

Purpose of the Study:

  • To design an edge service composition model utilizing edge computing principles.
  • To propose an optimization method for edge service composition based on the BAS algorithm.
  • To evaluate the proposed method's performance against existing heuristic and cloud-based approaches.

Main Methods:

  • Developed an edge service composition model within an edge computing framework.
  • Implemented the Bird Swarm Algorithm (BAS) for optimizing the selection and combination of edge services.
  • Compared the BAS-based method with Particle Swarm Optimization (PSO) and Weighted Particle Algorithm (WPA) heuristic methods, as well as traditional cloud service composition.

Main Results:

  • The BAS optimization algorithm demonstrated superior efficiency in edge service composition compared to PSO and WPA.
  • The proposed edge computing approach significantly reduced service response times.
  • The method resulted in lower operational costs and enhanced the quality of user experience.

Conclusions:

  • The BAS-based edge service composition model offers a more efficient and effective solution for edge computing environments.
  • This approach provides tangible benefits including reduced latency, cost savings, and improved user satisfaction.
  • The findings suggest a promising direction for optimizing distributed service delivery in edge networks.