{"title":"多云环境中有效服务供应的基于容器的云代理","authors":"Vinothiyalakshmi P., Rajganesh Nagarajan, Ramkumar Thirunavukarasu, Arun Pandian J., Evans Kotei","doi":"10.1155/int/1009713","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Container-based cloud brokers are third-party services that act as an intermediate entity between users and multiple cloud providers. The cloud brokers intended to perform discovery and provisioning of cloud services with an affordable pricing scheme. As cloud services can be provisioned on-demand basis for multiple users, the cloud brokers are unable to provide the most suited services to the users on time. To address this issue, the proposed work introduces a novel approach for efficient cloud service provisioning by utilizing container-based cloud service brokerage and implementing service arbitrage across various cloud providers. A microservice architecture-based service discovery mechanism is developed which incorporates a service registry for tracking newly available services from the providers. Docker containers are employed to orchestrate the services, which ensures streamlined management and deployment of offered services. Further, the proposed system recommends and evaluates the services to the cloud users based on probability matrices, mapping matrices, and user feedback. The performance of the proposed model is compared with existing techniques, namely, rough multidimensional matrix (RMDM) and similarity-enhanced hybrid group recommendation approach (HGRA). Experimental results show that the proposed model outperforms the existing models in terms of clustering accuracy and execution time.</p>\n </div>","PeriodicalId":14089,"journal":{"name":"International Journal of Intelligent Systems","volume":"2025 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/int/1009713","citationCount":"0","resultStr":"{\"title\":\"A Container-Based Cloud Broker for Effective Service Provisioning in Multicloud Environment\",\"authors\":\"Vinothiyalakshmi P., Rajganesh Nagarajan, Ramkumar Thirunavukarasu, Arun Pandian J., Evans Kotei\",\"doi\":\"10.1155/int/1009713\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p>Container-based cloud brokers are third-party services that act as an intermediate entity between users and multiple cloud providers. The cloud brokers intended to perform discovery and provisioning of cloud services with an affordable pricing scheme. As cloud services can be provisioned on-demand basis for multiple users, the cloud brokers are unable to provide the most suited services to the users on time. To address this issue, the proposed work introduces a novel approach for efficient cloud service provisioning by utilizing container-based cloud service brokerage and implementing service arbitrage across various cloud providers. A microservice architecture-based service discovery mechanism is developed which incorporates a service registry for tracking newly available services from the providers. Docker containers are employed to orchestrate the services, which ensures streamlined management and deployment of offered services. Further, the proposed system recommends and evaluates the services to the cloud users based on probability matrices, mapping matrices, and user feedback. The performance of the proposed model is compared with existing techniques, namely, rough multidimensional matrix (RMDM) and similarity-enhanced hybrid group recommendation approach (HGRA). Experimental results show that the proposed model outperforms the existing models in terms of clustering accuracy and execution time.</p>\\n </div>\",\"PeriodicalId\":14089,\"journal\":{\"name\":\"International Journal of Intelligent Systems\",\"volume\":\"2025 1\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/int/1009713\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/int/1009713\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/int/1009713","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A Container-Based Cloud Broker for Effective Service Provisioning in Multicloud Environment
Container-based cloud brokers are third-party services that act as an intermediate entity between users and multiple cloud providers. The cloud brokers intended to perform discovery and provisioning of cloud services with an affordable pricing scheme. As cloud services can be provisioned on-demand basis for multiple users, the cloud brokers are unable to provide the most suited services to the users on time. To address this issue, the proposed work introduces a novel approach for efficient cloud service provisioning by utilizing container-based cloud service brokerage and implementing service arbitrage across various cloud providers. A microservice architecture-based service discovery mechanism is developed which incorporates a service registry for tracking newly available services from the providers. Docker containers are employed to orchestrate the services, which ensures streamlined management and deployment of offered services. Further, the proposed system recommends and evaluates the services to the cloud users based on probability matrices, mapping matrices, and user feedback. The performance of the proposed model is compared with existing techniques, namely, rough multidimensional matrix (RMDM) and similarity-enhanced hybrid group recommendation approach (HGRA). Experimental results show that the proposed model outperforms the existing models in terms of clustering accuracy and execution time.
期刊介绍:
The International Journal of Intelligent Systems serves as a forum for individuals interested in tapping into the vast theories based on intelligent systems construction. With its peer-reviewed format, the journal explores several fascinating editorials written by today''s experts in the field. Because new developments are being introduced each day, there''s much to be learned — examination, analysis creation, information retrieval, man–computer interactions, and more. The International Journal of Intelligent Systems uses charts and illustrations to demonstrate these ground-breaking issues, and encourages readers to share their thoughts and experiences.