Secure and economical multi-cloud storage policy with NSGA-II-C

Secure and economical multi-cloud storage policy with NSGA-II-C
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NSGA-II-C 安全且经济的多云存储策略

DOI:
10.1016/j.asoc.2019.105649
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发表时间:
2019-10
影响因子:
8.7
通讯作者:
Liu Tieqiao
Liu Tieqiao
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yang Jie;Zhu Haibin;Liu Tieqiao

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多云计算是一项具有吸引力的技术,其原因包括用户数据的安全性。这项工作提供了一个与多云存储(MCS)相关的问题的解决方案,即如何基于多目标优化在不同云服务提供商之间分配部分数据,同时以最小的存储成本保持高度的安全性和性能。采用具有特殊组合过程的非支配排序遗传算法II (NSGA-II-C)求解该问题。通过对实验结果的统计分析,对比MOEA/D和SPEA2, NSGA-II-C在解决本文提出的问题上具有更好的代距和多样性性能。将该方法与MCS和单一云存储的类似研究进行了比较。实验结果表明,所得到的最优解在安全性、成本和性能上都优于同类研究。此外,还详细分析了Pareto前线各目标之间的关系。
Multi-cloud computing is an attractive technology for many reasons including user’s data security. This work offers a solution to the problem relative to Multi-Cloud Storage (MCS), i.e., how to allocate partial data among different cloud service providers based on multi-objective optimization while maintaining a high degree of security and performance at the minimal storage cost. Non-dominated Sorting Genetic Algorithm II with a special process of Combinations (NSGA-II-C), is adopted to solve the problem. NSGA-II-C has better performance of generational distance and diversity by comparing with MOEA/D and SPEA2 in solving the proposed problem based on the statistical analysis of experimental results. The proposed method is compared with the similar studies of MCS and single cloud storage. Experimental results show that the obtained optimal solution outperforms similar studies at security, cost and performance. In addition, the relations between objectives in the Pareto front are analyzed in detail.
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