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Federated learning inspired Antlion based orchestration for Edge computing environment.

Madhusudhan H S1, Punit Gupta2,3

  • 1Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, Karnataka, India.

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|June 4, 2024
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Summary
This summary is machine-generated.

An Artificial Neural Network (ANN) inspired Antlion algorithm optimizes task orchestration in Edge computing. This approach enhances resource utilization and reduces energy consumption for IoT devices, improving overall system efficiency.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Distributed Systems

Background:

  • Edge computing architectures are crucial for processing Internet of Things (IoT) data closer to the source.
  • Effective resource management and task scheduling are critical challenges in Fog-Edge environments.
  • Optimizing resource utilization and energy consumption is essential for scalable Edge deployments.

Purpose of the Study:

  • To propose an Artificial Neural Network (ANN) inspired Antlion algorithm for task orchestration in Edge computing environments.
  • To enhance resource utilization and reduce energy consumption in Edge and cloud layers.
  • To evaluate the proposed algorithm's performance against existing methods, particularly for healthcare applications.

Main Methods:

  • Development of an Artificial Neural Network (ANN) inspired Antlion algorithm for task scheduling.
  • Implementation of the algorithm in an Edge computing environment, focusing on resource allocation.
  • Comparative analysis with Fuzzy Logic and Round Robin algorithms using key performance metrics.

Main Results:

  • The proposed ANN-Antlion algorithm significantly improves load balancing across Edge and cloud layers.
  • Demonstrated substantial reductions in cloud energy consumption (95.94%) and Edge energy consumption (16.79%).
  • Achieved improvements in CPU utilization (19.85% Edge, 10.64% cloud), network utilization (23.33%), and a significant decrease in average waiting time (96% vs. Fuzzy Logic).

Conclusions:

  • The ANN-inspired Antlion algorithm offers a superior approach to task orchestration in Edge computing.
  • The algorithm effectively balances workloads, leading to enhanced efficiency and reduced energy demands.
  • The proposed method shows significant advantages over existing algorithms, particularly for resource-intensive applications like healthcare.