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Related Experiment Video

Updated: Oct 12, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Dynamic computation offloading algorithm based on particle swarm optimization with a mutation operator in

Yanpei Liu¹, Wei Huang¹, Liping Wang¹

¹School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.

Mathematical Biosciences and Engineering : MBE

|November 24, 2021

Summary

This summary is machine-generated.

This study introduces a dynamic computation offloading algorithm (DCO-PSOMO) for multi-access edge computing. It optimizes offloading decisions to reduce costs, conserve energy, and enhance user quality of service (QoS).

Keywords:

computation offloading multi-access edge computing offloading success rate overload time

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Area of Science:

Mobile Computing
Edge Computing
Optimization Algorithms

Background:

Existing mobile cloud computation offloading algorithms neglect critical factors like offloading opportunity selection, uninstall frequency, resource waste, and energy efficiency.
These oversights negatively impact the success probability of user offloading and overall system performance.

Purpose of the Study:

To propose a novel dynamic computation offloading algorithm (DCO-PSOMO) utilizing particle swarm optimization with a mutation operator.
To enhance offloading decisions in multi-access edge computing environments by considering dynamic system states and user behavior.

Main Methods:

Dynamically determining mobile terminal overload times using CPU and memory utilization rates via locally weighted regression.
Predicting offloading success probability based on user dwell time and edge computing communication range.
Developing a computation offloading model incorporating response time and energy consumption, optimized using particle swarm optimization with mutation.

Main Results:

The DCO-PSOMO algorithm effectively reduces offloading costs and mobile terminal energy consumption.
Demonstrates significant improvements in the probability of successful offloading.
Enhances the overall quality of service (QoS) for mobile users compared to existing algorithms (JOCAP, ECOMC, ESRLR).

Conclusions:

The proposed DCO-PSOMO algorithm provides a superior approach to dynamic computation offloading in multi-access edge computing.
It addresses the limitations of previous methods by optimizing resource utilization, energy efficiency, and user experience.