article

Resource Scheduling in Fog Environment Using Optimization Algorithms for 6G Networks

Authors:

Rajeev TiwariAuthors Info & Claims

International Journal of Software Science and Computational Intelligence (IJSSCI), Volume 14, Issue 1

Pages 1 - 24

https://doi.org/10.4018/IJSSCI.304440

Published: 13 July 2022 Publication History

Abstract

In the traditional system, various researchers have suggested different resource scheduling and optimization algorithms. However, still, there is a scope to reduce Bandwidth, latency, energy consumption, and total communication cost in the Fog environment. in this work discussion is done on various performance challenges that are experienced in the Fog Environment based on 6G networks and explore the role of optimization techniques to overcome these challenges This work is focused on the Comparison of PSO, GA, and Round-Robin algorithm on parameters Cost, makespan, average execution time, and energy consumption for the resource management in the Fog environment. This study also represents which technique among the Group behavior species, Social Behaviour, and Pre-emptive type is better for achieving QoS for resource management in the Fog environment for the 6G network. In this work, we have discussed various resource scheduling problems that may be faced in the future, and what type of improvement can be considered in terms of IoT devices and 6G networks.

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Cited By

Chui KSaini DMishra ASiddharth DJoshi PBansal RBansal S(2023)Development of Enhanced Chimp Optimization Algorithm (OFCOA) in Cognitive Radio Networks for Energy Management and Resource AllocationInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.33589815:1(1-20)Online publication date: 27-Jan-2023
https://dl.acm.org/doi/10.4018/IJSSCI.335898
Goel GTiwari R(2023)Resource Scheduling Techniques for Optimal Quality of Service in Fog Computing Environment: A ReviewWireless Personal Communications: An International Journal10.1007/s11277-023-10421-4131:1(141-164)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1007/s11277-023-10421-4
Kumar RSingh SRao U(2022)Multi-Objective Energy-Efficient Virtual Machine Consolidation Using Dynamic Double Threshold-Enhanced Search and Rescue-Based OptimizationInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.31500614:1(1-26)Online publication date: 2-Dec-2022
https://dl.acm.org/doi/10.4018/IJSSCI.315006
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Index Terms

Resource Scheduling in Fog Environment Using Optimization Algorithms for 6G Networks
1. General and reference
  1. Cross-computing tools and techniques
2. Networks
  1. Network services
    1. Network management
  2. Network types
    1. Mobile networks
    2. Wireless access networks

Index terms have been assigned to the content through auto-classification.

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cover image International Journal of Software Science and Computational Intelligence

International Journal of Software Science and Computational Intelligence Volume 14, Issue 1

Oct 2022

1068 pages

ISSN:1942-9045

EISSN:1942-9037

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Copyright © 2022.

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IGI Global

United States

Publication History

Published: 13 July 2022

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Cited By

Chui KSaini DMishra ASiddharth DJoshi PBansal RBansal S(2023)Development of Enhanced Chimp Optimization Algorithm (OFCOA) in Cognitive Radio Networks for Energy Management and Resource AllocationInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.33589815:1(1-20)Online publication date: 27-Jan-2023
https://dl.acm.org/doi/10.4018/IJSSCI.335898
Goel GTiwari R(2023)Resource Scheduling Techniques for Optimal Quality of Service in Fog Computing Environment: A ReviewWireless Personal Communications: An International Journal10.1007/s11277-023-10421-4131:1(141-164)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1007/s11277-023-10421-4
Kumar RSingh SRao U(2022)Multi-Objective Energy-Efficient Virtual Machine Consolidation Using Dynamic Double Threshold-Enhanced Search and Rescue-Based OptimizationInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.31500614:1(1-26)Online publication date: 2-Dec-2022
https://dl.acm.org/doi/10.4018/IJSSCI.315006
Kumar RSingh SRao U(2022)Multi-Objective Adaptive Manta-Ray Foraging Optimization for Workflow Scheduling with Selected Virtual Machines Using Time-Series-Based PredictionInternational Journal of Software Science and Computational Intelligence10.4018/IJSSCI.31255914:1(1-25)Online publication date: 25-Oct-2022
https://dl.acm.org/doi/10.4018/IJSSCI.312559

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