{"title":"C-DRM:解决云服务选择不确定性的合并P-TOPSIS熵技术","authors":"K. Nivitha, Pabitha Parameshwaran","doi":"10.5755/j01.itc.51.3.30881","DOIUrl":null,"url":null,"abstract":"Cloud Computing is diversified with its services exponentially and lured large number of consumers towards the technology indefinitely. It has become a highly challenging problem to satiate the user requirements. Most of the existing system ingest large search space or provide inappropriate service; hence, there is a need for the reliable and space competent service selection/ranking in the cloud environment. The proposed work introduces a novel pruning method and Dual Ranking Method (DRM) to rank the services from n services in terms of space conserving and providing reliable service quenching the user requirements as well. Dual Ranking Method (DRM) is proposed focusing on the uncertainty of user preferences along with their priorities; converting it to weights with the use of Jensen-Shannon (JS) Entropy Function. The ranking of service is employed through Priority-Technique for Order of Preference by Similarity to Ideal Solution (P-TOPSIS) and space complexity is reduced by novel Utility Pruning method. The performance of the proposed work Clustering – Dual Ranking Method (C-DRM) is estimated in terms of accuracy, Closeness Index (CI) and space complexity have been validated through case study where results outperforms the existing approaches","PeriodicalId":54982,"journal":{"name":"Information Technology and Control","volume":"38 1","pages":"592-605"},"PeriodicalIF":2.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"C-DRM: Coalesced P-TOPSIS Entropy Technique addressing Uncertainty in Cloud Service Selection\",\"authors\":\"K. Nivitha, Pabitha Parameshwaran\",\"doi\":\"10.5755/j01.itc.51.3.30881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud Computing is diversified with its services exponentially and lured large number of consumers towards the technology indefinitely. It has become a highly challenging problem to satiate the user requirements. Most of the existing system ingest large search space or provide inappropriate service; hence, there is a need for the reliable and space competent service selection/ranking in the cloud environment. The proposed work introduces a novel pruning method and Dual Ranking Method (DRM) to rank the services from n services in terms of space conserving and providing reliable service quenching the user requirements as well. Dual Ranking Method (DRM) is proposed focusing on the uncertainty of user preferences along with their priorities; converting it to weights with the use of Jensen-Shannon (JS) Entropy Function. The ranking of service is employed through Priority-Technique for Order of Preference by Similarity to Ideal Solution (P-TOPSIS) and space complexity is reduced by novel Utility Pruning method. The performance of the proposed work Clustering – Dual Ranking Method (C-DRM) is estimated in terms of accuracy, Closeness Index (CI) and space complexity have been validated through case study where results outperforms the existing approaches\",\"PeriodicalId\":54982,\"journal\":{\"name\":\"Information Technology and Control\",\"volume\":\"38 1\",\"pages\":\"592-605\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Technology and Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.5755/j01.itc.51.3.30881\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Technology and Control","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.5755/j01.itc.51.3.30881","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
C-DRM: Coalesced P-TOPSIS Entropy Technique addressing Uncertainty in Cloud Service Selection
Cloud Computing is diversified with its services exponentially and lured large number of consumers towards the technology indefinitely. It has become a highly challenging problem to satiate the user requirements. Most of the existing system ingest large search space or provide inappropriate service; hence, there is a need for the reliable and space competent service selection/ranking in the cloud environment. The proposed work introduces a novel pruning method and Dual Ranking Method (DRM) to rank the services from n services in terms of space conserving and providing reliable service quenching the user requirements as well. Dual Ranking Method (DRM) is proposed focusing on the uncertainty of user preferences along with their priorities; converting it to weights with the use of Jensen-Shannon (JS) Entropy Function. The ranking of service is employed through Priority-Technique for Order of Preference by Similarity to Ideal Solution (P-TOPSIS) and space complexity is reduced by novel Utility Pruning method. The performance of the proposed work Clustering – Dual Ranking Method (C-DRM) is estimated in terms of accuracy, Closeness Index (CI) and space complexity have been validated through case study where results outperforms the existing approaches
期刊介绍:
Periodical journal covers a wide field of computer science and control systems related problems including:
-Software and hardware engineering;
-Management systems engineering;
-Information systems and databases;
-Embedded systems;
-Physical systems modelling and application;
-Computer networks and cloud computing;
-Data visualization;
-Human-computer interface;
-Computer graphics, visual analytics, and multimedia systems.