Cloud Computing Demand Elasticity Algorithm based on Ant Colony Algorithm

Author:

Liu Chunyu1,Mu Fengrui1,Zhang Weilong2

Affiliation:

1. College of Computer Science and Engineering, Cangzhou, Normal University, Hebei, Cangzhou 061000, China

2. Quality Management Center, Hebei Jiaotong Vocational and Technical, Shijiazhuang, Hebei 050035, China

Abstract

Background: In the recent era of technology, the traditional Ant Colony Algorithm (ACO) is insufficient in solving the problem of network congestion and load balance, and network utilization. Methods: This paper proposes an improved ant colony algorithm, which considers the price factor based on the theory of elasticity of demand. The price factor is denominated in the impact on the network load which means indirect control of network load, congestion or auxiliary solution to calculate the idle resources caused by the low network utilization and reduced profits. Results: Experimental results show that the improved algorithm can balance the overall network load, extend the life of path by nearly 3 hours, greatly reduce the risk of network paralysis, and increase the profit of the manufacturer by 300 million Yuan. Conclusion: Furthermore, the results show that the improved method has great application value in improving network efficiency, balancing network load, prolonging network life and increasing network operating profit.

Funder

“Tiancheng Huizhi” Innovation and Education fund of the Ministry of Education

Publisher

Bentham Science Publishers Ltd.

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Cited by 2 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. Research on the hybrid chaos-coud salp swarm algorithm;Communications in Nonlinear Science and Numerical Simulation;2024-11

2. Improved Design of Computer Network Based on Ant Colony Algorithm;2023 4th International Conference for Emerging Technology (INCET);2023-05-26

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3