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| 一种成本相关的云提供商数据可靠性保证算法 |
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钟睿明1,2, 刘川意3,2, 王春露1,2, 项菲1,2
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1.北京邮电大学 计算机学院, 北京 100876;2.可信分布式计算与服务教育部重点实验室（北京邮电大学）, 北京 100876;3.北京邮电大学 软件学院, 北京 100876
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| 摘要: |
| 数据可靠性保证和容灾成本控制对云提供商而言是一个相互矛盾的问题.在分析已有数据保障机制的基础上，设计了一个基于多个云平台的分布式富云容灾模型，利用富云容灾系统，私有云提供商可以借用其他云平台的虚拟资源对自身数据进行冗余备份.为了减少数据传输的响应时间，富云容灾模型通过设置多个地理位置隔离的富云代理实现云平台用户任务的分配，减少私有云平台的工作负荷.针对富云容灾系统的成本优化和数据可靠性保证问题，提出了一种成本相关的云计算服务数据可靠性保证算法CAHRPA.该算法根据数据传输带宽和容灾费用在多个云平台中动态选择数据副本的存放位置，从而以一种成本优化的方式为云提供商提供数据容灾方案.实验结果表明，CAHRPA 能够在保证数据可靠性的同时，实现一种成本更低的数据容灾策略. |
| 关键词: 云计算 数据可靠性 容灾 差分进化 云存储 |
| DOI：10.13328/j.cnki.jos.004498 |
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| 基金项目:国家自然科学基金（60973009）；国家重大科技专项（2012ZX03005010） |
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| Cost-Aware Data Reliability Provision Algorithm for the Cloud Providers |
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ZHONG Rui-Ming1,2, LIU Chuan-Yi3,2, WANG Chun-Lu1,2, XIANG Fei1,2
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1.School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;2.Key Laboratory of Trustworthy Distributed Computing and Service of Ministry of Education (Beijing University of Posts and Telecommunications), Beijing 100876, China;3.School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
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| Abstract: |
| Data availability is a desirable feature for all cloud providers. However, adoption of disaster recovery will bring incremental cost due to the continued investment of hardware. This paper illustrates the existing assurance mechanisms for data reliability and points out that the data availability and disaster recovery cost are always two incompatible goals for cloud providers. A rich cloud based disaster recovery (DR) model is designed for cloud providers. In this model, multiple rich cloud proxies are employed in order to reduce the response time and improve the quality of service. With help of this system, a cloud provider is able to replicate data with lower cost by utilizing the virtual resource from other clouds. In order to minimize the DR cost while guaranteeing the data availability, a cost aware high data reliability provision algorithm (CAHRPA) is proposed to tackle such an optimization problem. In the end, the feasibility and efficiency of this CAHRPA is verified by the comparison with some other replication strategies. |
| Key words: cloud computing data reliability disaster recovery differential evolution cloud storage |
