{"title":"Optimal Data Allocation in the Environment of Edge and Cloud Servers","authors":"Chengyu Peng, Haibin Zhu, Linyuan Liu, R. Grewal","doi":"10.1109/ICNSC55942.2022.10004065","DOIUrl":null,"url":null,"abstract":"With the rise in popularity of cloud computing, there is a growing trend toward the storage of data in a cloud environment. However, there is a significant increase in the risk of privacy information leakage, and users could face serious challenges as a result of data leakage. In this paper, we propose an allocation scheme for the storage of data in a collaborative edge-cloud environment, with a focus on enhanced data privacy. Specifically, we first divide the datasets by fields to eliminate as much as possible the correlation between the leaked data. We then evaluate the sensitivity of the data and server trust to calculate the degree of fitting between them and combine the results with the performance score to obtain a server qualification value for the stored fields. Several constraints are also specified, and the E-CARGO model is used to formalize the problem. Based on the qualification value, we can find the optimal allocation using the IBM ILOG CPLEX Optimization (CPLEX) Package. In our experiments, our proposed solution allows the data to be stored in servers that better suit their requirements, while reducing the user overhead.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSC55942.2022.10004065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the rise in popularity of cloud computing, there is a growing trend toward the storage of data in a cloud environment. However, there is a significant increase in the risk of privacy information leakage, and users could face serious challenges as a result of data leakage. In this paper, we propose an allocation scheme for the storage of data in a collaborative edge-cloud environment, with a focus on enhanced data privacy. Specifically, we first divide the datasets by fields to eliminate as much as possible the correlation between the leaked data. We then evaluate the sensitivity of the data and server trust to calculate the degree of fitting between them and combine the results with the performance score to obtain a server qualification value for the stored fields. Several constraints are also specified, and the E-CARGO model is used to formalize the problem. Based on the qualification value, we can find the optimal allocation using the IBM ILOG CPLEX Optimization (CPLEX) Package. In our experiments, our proposed solution allows the data to be stored in servers that better suit their requirements, while reducing the user overhead.