Optimal Data Allocation in the Environment of Edge and Cloud Servers

Chengyu Peng, Haibin Zhu, Linyuan Liu, R. Grewal
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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.
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边缘和云服务器环境下的数据优化分配
随着云计算的普及,在云环境中存储数据的趋势越来越大。但是,隐私信息泄露的风险显著增加,用户可能会因为数据泄露而面临严重的挑战。在本文中,我们提出了一种在协作边缘云环境中存储数据的分配方案,重点是增强数据隐私。具体来说,我们首先将数据集按字段划分,以尽可能地消除泄漏数据之间的相关性。然后,我们评估数据的敏感性和服务器信任,以计算它们之间的拟合程度,并将结果与性能分数结合起来,以获得存储字段的服务器资格值。提出了约束条件,并利用E-CARGO模型对问题进行了形式化描述。根据限定值,使用IBM ILOG CPLEX优化包(CPLEX)找到最优分配。在我们的实验中,我们提出的解决方案允许将数据存储在更适合其需求的服务器中,同时减少用户开销。
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