arrow
返回

CBWO: A Novel Multi-objective Load Balancing Technique for Cloud Computing

delete2025-03-01
delete0
PRE
AI
H
Hayyolalam, Vahideh *
Ö
Öznur Özkasap
DOI:10.1016/j.future.2024.107561delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
In cloud computing systems, the growing demand for diverse applications has led to challenges in resource allocation and workload distribution, resulting in increased energy consumption and computational costs. To address these challenges, we propose a novel load-balancing method, namely CBWO, that integrates Chaos theory with the Black Widow Optimization algorithm. Our approach is designed to optimize cloud computing environments by improving energy efficiency and resource utilization. We employ CloudSim for simulations, evaluating key performance metrics such as energy consumption, resource utilization, makespan, task completion time, and imbalance degree. The experimental results demonstrate the superiority of our method, achieving average improvements of 67.28% in makespan and 29.03% in energy consumption compared to existing solutions.
Keyword:
Cloudsim
Distributed systems
Energy efficiency
Meta-heuristics
Resource utilization

期刊

F
Future Generation Computer Systems-The International Journal of eScience
IF:
6.1
论文数:
6.9K
被引数:
2.3W

机构

K
koc university
学者数:
5.7K
论文数: 4.5K
被引数: 48
引用论文

引用论文

Introduced and native plant species composition of vacant unmanaged green roofs in New York City
err2020-04-30
err0
PREAI
errJason M. Aloisio; Matthew I. Palmer; Amy R. Tuininga; J. D. Lewis
err分享
err收藏
err分享
err收藏
Improvement of tasks scheduling algorithm based on load balancing candidate method under cloud computing environment
err2023-02-01
err19
PREAI
errChiang, Mao-Lun; Hsieh, Hui-Ching; Cheng, Yu-Huei; Lin, Wei-Ling; Zeng, Bo-Hao
err分享
err收藏
学者 查看更多内容