A New Integrated Approach for Cloud Service Composition and Sharing Using a Hybrid Algorithm

4区工程技术 Q1 Mathematics

Mathematical Problems in Engineering Pub Date : 2024-02-12 DOI:10.1155/2024/3136546

Jayaudhaya J., Jayaraj R., Ramash Kumar K.

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引用次数: 0

Abstract

The concept of a “Smart City” emphasizes the need to employ information and communication technologies to strengthen the quality, connectivity, and efficiency of various municipal services. Cloud computing and the Internet of Things are shaping future tech. Both ideas greatly impact smart city application and solution development. Cloud computing is amazing at managing and storing remote service access. Several companies have switched to cloud leasing to reduce local resource burden. Due to the intricacy and flexibility of cloud-maintained services, selecting jobs that best suit client needs should be optimized. Quality of service criteria for each cloud service are the best tools for choosing and optimizing cloud carriers. Genetic algorithms (GAs) and ant colony optimization (ACO) are combined to make cloud computing. It is discovered that the recommended ACO + GA obtains an accuracy of 82% when compared to existing methods of energy- and reliability-aware multiobjective optimization method and the hybrid cuckoo particles swarm, artificial bee colony optimization (CPS + ABCO) where accuracy is 68% and 75%, respectively.

查看原文本刊更多论文

使用混合算法的云服务合成与共享综合新方法

智慧城市 "的概念强调需要利用信息和通信技术来提高各种市政服务的质量、连通性和效率。云计算和物联网正在塑造未来的技术。这两种理念都对智慧城市应用和解决方案的开发产生了重大影响。云计算在管理和存储远程服务访问方面表现出色。一些公司已经转向云租赁，以减轻本地资源负担。由于云维护服务的复杂性和灵活性，应优化选择最适合客户需求的工作。每种云服务的服务质量标准是选择和优化云载体的最佳工具。遗传算法（GA）和蚁群优化（ACO）被结合到云计算中。研究发现，与现有的能量和可靠性感知多目标优化方法以及混合布谷鸟粒子群、人工蜂群优化（CPS + ABCO）方法（准确率分别为 68% 和 75%）相比，推荐的 ACO + GA 获得了 82% 的准确率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Problems in Engineering 工程技术-工程：综合

CiteScore

4.00

自引率

0.00%

发文量

2853

审稿时长

4.2 months

期刊介绍： Mathematical Problems in Engineering is a broad-based journal which publishes articles of interest in all engineering disciplines. Mathematical Problems in Engineering publishes results of rigorous engineering research carried out using mathematical tools. Contributions containing formulations or results related to applications are also encouraged. The primary aim of Mathematical Problems in Engineering is rapid publication and dissemination of important mathematical work which has relevance to engineering. All areas of engineering are within the scope of the journal. In particular, aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, industrial engineering and manufacturing systems, and mechanical engineering are of interest. Mathematical work of interest includes, but is not limited to, ordinary and partial differential equations, stochastic processes, calculus of variations, and nonlinear analysis.