Bi-Objective simplified swarm optimization for fog computing task scheduling

Author:

Yeh Wei-Chang,Liu Zhenyao,Tseng Kuan-Cheng

Abstract

In the face of burgeoning data volumes, latency issues present a formidable challenge to cloud computing. This problem has been strategically tackled through the advent of fog computing, shifting computations from central cloud data centers to local fog devices. This process minimizes data transmission to distant servers, resulting in significant cost savings and instantaneous responses for users. Despite the urgency of many fog computing applications, existing research falls short in providing time-effective and tailored algorithms for fog computing task scheduling. To bridge this gap, we introduce a unique local search mechanism, Card Sorting Local Search (CSLS), that augments the non-dominated solutions found by the Bi-objective Simplified Swarm Optimization (BSSO). We further propose Fast Elite Selecting (FES), a ground-breaking one-front non-dominated sorting method that curtails the time complexity of non-dominated sorting processes. By integrating BSSO, CSLS, and FES, we are unveiling a novel algorithm, Elite Swarm Simplified Optimization (EliteSSO), specifically developed to conquer time-efficiency and non-dominated solution issues, predominantly in large-scale fog computing task scheduling conundrums. Computational evidence reveals that our proposed algorithm is both highly efficient in terms of time and exceedingly effective, outstripping other algorithms on a significant scale.

Publisher

Growing Science

Subject

Industrial and Manufacturing Engineering

Reference1 articles.

1. Bi-Objective simplified swarm optimization for fog computing task scheduling;Yeh;International Journal of Industrial Engineering Computations,2023

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Simplified swarm optimisation for CNN hyperparameters: a sound classification approach;International Journal of Web and Grid Services;2024

2. PaF & MbOTS: Novel Task Scheduling Strategies for Fog Computing Environment;2023 6th International Conference on Recent Trends in Advance Computing (ICRTAC);2023-12-14

3. Bi-Objective simplified swarm optimization for fog computing task scheduling;International Journal of Industrial Engineering Computations;2023

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