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LITO: Lemur-Inspired Task Offloading for Edge-Fog-Cloud Continuum Systems.

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  • 1Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces LITO, a novel lemur-inspired task offloading algorithm for edge, fog, and cloud systems. LITO enhances energy efficiency and resource utilization by mimicking lemur social behaviors for task assignment and scheduling.

Keywords:
Internet of Thingsedge computingedge–fog–cloud continuumfog computingresource managementsupervised policy learningtask offloading

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Artificial Intelligence

Background:

  • Edge, fog, and cloud continuum architectures face challenges with heterogeneous, latency-sensitive workloads, energy consumption, and resource utilization.
  • Classical task offloading methods lack adaptability or incur high computational overhead and centralized coordination.

Purpose of the Study:

  • To propose LITO, a lemur-inspired task offloading algorithm for edge, fog, and cloud continuum systems.
  • To address challenges in energy consumption, resource utilization, and latency for dynamic workloads.

Main Methods:

  • LITO models the infrastructure as a social system with nodes assuming distinct roles.
  • It incorporates lemur-inspired mechanisms: energy-aware task assignment (sun basking) and cooperative scheduling (huddling).
  • A continual supervised policy-learning layer with contextual bandit feedback refines offloading decisions.

Main Results:

  • LITO jointly minimizes energy consumption and deadline violations while maximizing resource utilization and throughput.
  • Simulations show LITO outperforms existing multi-objective offloading baselines.
  • The algorithm excels in energy consumption, resource utilization, latency, SLA violations, and throughput under congested scenarios.

Conclusions:

  • LITO offers an effective, bio-inspired approach to task offloading in complex continuum environments.
  • The lemur-inspired mechanisms provide adaptability and efficiency in dynamic, high-load conditions.
  • LITO demonstrates significant improvements over traditional offloading strategies.