. In order to perfectly meet the needs of business leaders, decision-makers have resorted to the integration of external sources (such as Linked Open Data) in the decision-making system in order to enrich their existing data warehouses with new concepts contributing to bring added value to their organizations, enhance its productivity and retain its customers. However, the traditional data warehouse environment is not suitable to support external Big Data. To deal with this new challenge, several researches are oriented towards the direct conversion of classical relational data warehouse to a columnar NoSQL data warehouse, whereas the existing advanced works based on clustering algorithms are very limited and have several shortcomings. In this context, our paper proposes a new solution that conceives an optimized columnar data warehouse based on CLARANS clustering algorithm that has proven its effectiveness in generating optimal column families. Experimental re-sults improve the validity of our system by performing a detailed comparative study between the existing advanced approaches and our proposed optimized method.
． 为了完美地满足商业领袖的需求，决策者在决策系统中采用了外部资源(如Linked Open Data)的集成，以便用新的概念丰富他们现有的数据仓库，从而为他们的组织带来附加价值，提高其生产力并保留其客户。然而，传统的数据仓库环境并不适合支持外部大数据。为了应对这一新的挑战，一些研究面向将经典关系数据仓库直接转换为列式NoSQL数据仓库，而现有的基于聚类算法的先进工作非常有限，并且存在一些不足。在此背景下，本文提出了一种新的解决方案，即基于CLARANS聚类算法构想一个优化的列数据仓库，该算法已被证明在生成最优列族方面是有效的。实验结果通过对现有的先进方法和本文提出的优化方法进行了详细的对比研究，提高了系统的有效性。
{"title":"Optimization of Columnar NoSQL Data Warehouse Model with Clarans Clustering Algorithm","authors":"N. Soussi","doi":"10.31577/cai_2023_3_762","DOIUrl":"https://doi.org/10.31577/cai_2023_3_762","url":null,"abstract":". In order to perfectly meet the needs of business leaders, decision-makers have resorted to the integration of external sources (such as Linked Open Data) in the decision-making system in order to enrich their existing data warehouses with new concepts contributing to bring added value to their organizations, enhance its productivity and retain its customers. However, the traditional data warehouse environment is not suitable to support external Big Data. To deal with this new challenge, several researches are oriented towards the direct conversion of classical relational data warehouse to a columnar NoSQL data warehouse, whereas the existing advanced works based on clustering algorithms are very limited and have several shortcomings. In this context, our paper proposes a new solution that conceives an optimized columnar data warehouse based on CLARANS clustering algorithm that has proven its effectiveness in generating optimal column families. Experimental re-sults improve the validity of our system by performing a detailed comparative study between the existing advanced approaches and our proposed optimized method.","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"2 1","pages":"762-780"},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70010172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning to Translate Kannada and English Queries for Mixed Script Information Retrieval","authors":"S. SowmyaLakshmiB., R. ShambhaviB.","doi":"10.31577/cai_2021_3_628","DOIUrl":"https://doi.org/10.31577/cai_2021_3_628","url":null,"abstract":"","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"40 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70009850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real Time Mobile Ad Investigator: An Effective and Novel Approach for Mobile Click Fraud Detection","authors":"Iroshan Aberathne, C. Walgampaya","doi":"10.31577/cai_2021_3_606","DOIUrl":"https://doi.org/10.31577/cai_2021_3_606","url":null,"abstract":"","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"40 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70009832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-24DOI: 10.31577/cai_2020_1-2_83
Shanchen Pang, Dong Dekun, Shuyu Wang
Energy consumption is an important cost driven by growth of computing power, thereby energy conservation has become one of the major problems faced by cloud system. How to maximize the utilization of physical machines, reduce the number of virtual machine migrations, and maintain load balance under the constraints of physical machine resource thresholds that is the effective way to implement energy saving in data center. In the paper, we propose a multi-objective physical model for virtual machine deployment. Then the improved multi-objective particle swarm optimization (TPSO) is applied to virtual machine deployment. Compared to other algorithms, the algorithm has better ergodicity into the initial stage, improves the optimization precision and optimization efficiency of the particle swarm. The experimental results based on CloudSim simulation platform show that the algorithm is effective at improving physical machine resource utilization, reducing resource waste, and improving system load balance.
{"title":"Virtual Machine Deployment Strategy Based on Improved PSO in Cloud Computing","authors":"Shanchen Pang, Dong Dekun, Shuyu Wang","doi":"10.31577/cai_2020_1-2_83","DOIUrl":"https://doi.org/10.31577/cai_2020_1-2_83","url":null,"abstract":"Energy consumption is an important cost driven by growth of computing power, thereby energy conservation has become one of the major problems faced by cloud system. How to maximize the utilization of physical machines, reduce the number of virtual machine migrations, and maintain load balance under the constraints of physical machine resource thresholds that is the effective way to implement energy saving in data center. In the paper, we propose a multi-objective physical model for virtual machine deployment. Then the improved multi-objective particle swarm optimization (TPSO) is applied to virtual machine deployment. Compared to other algorithms, the algorithm has better ergodicity into the initial stage, improves the optimization precision and optimization efficiency of the particle swarm. The experimental results based on CloudSim simulation platform show that the algorithm is effective at improving physical machine resource utilization, reducing resource waste, and improving system load balance.","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2020-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47835857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.31577/cai_2019_6_1320
José Agustín Tortolero Osuna, A. J. Rosales Silva
{"title":"Parallel Peer Group Filter for Impulse Denoising in Digital Images on GPU","authors":"José Agustín Tortolero Osuna, A. J. Rosales Silva","doi":"10.31577/cai_2019_6_1320","DOIUrl":"https://doi.org/10.31577/cai_2019_6_1320","url":null,"abstract":"","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70009619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Review of Smart Contracts for Cloud-Based Manufacturing","authors":"A. H. Afridi","doi":"10.31577/cai_2022_1_34","DOIUrl":"https://doi.org/10.31577/cai_2022_1_34","url":null,"abstract":"","PeriodicalId":55215,"journal":{"name":"Computing and Informatics","volume":"41 1","pages":"34-55"},"PeriodicalIF":0.7,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70009914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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