高效的移动云存储:一种基于网络编码的方法

Jiajie Shen, Yi Li, Yangfan Zhou, Xin Wang
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引用次数: 2

摘要

云的云存储是确保分布式数据存储的安全性和可靠性的可行手段,其中数据在多个云中进行加密、编码和存储。然而,在移动设备(例如智能手机)中采用这种范式是一个巨大的挑战。由于移动设备中的资源有限,移动设备通常无法执行这种范例中所需的重量级操作(即数据加密、编码和传输)。本文的重点是解决这一挑战,即提高移动云的云存储系统中的数据存储性能。我们建议的关键是允许低功能的移动设备将计算和传输开销转移到云端。换句话说,我们提出了一种基于网络编码的云存储(NCCS)方案,其中云可以协作编码和交换数据。我们考虑了两种最先进的云的云存储方法,即AONT-RS和CAONT-RS,作为部署我们方案的示例案例。因此,我们提出了基于网络编码的增强,即NAONT-RS和NCAONT-RS。我们实现了一个原型的云的云系统来验证我们的建议的效率。我们将原型部署在Microsoft Azure上,并使用真实世界的痕迹进行了广泛的实验。实验结果表明,与AONT-RS和CAONT-RS相比,NAONT-RS和NCAONT-RS的数据存储时间最多减少50%,吞吐量最多提高110%。
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Mobile Cloud-of-Clouds Storage Made Efficient: A Network Coding Based Approach
Cloud-of-clouds storage is a viable means to ensure security and reliability of distributed data storage, where data are encrypted, encoded, and stored in multiple clouds. However, it is a great challenge to adopt such a paradigm in mobile devices (e.g., smartphone). Mobile devices are generally incapable to perform the heavy-weight operations (i.e., data encryption, encoding, and transmission) required in such a paradigm, given the limited resources in such devices. This paper focuses on addressing this challenge, i.e., improving data storage performance in mobile cloud-of-clouds storage systems. The key of our proposal is to allow the low-capability mobile devices to offload the computational and transmission overhead to the clouds. In other words, we propose a Network Coding based Cloud-of-clouds Storage (NCCS) scheme, where the clouds can encode and exchange data collaboratively. We consider two state-of-the-art cloud-of-clouds storage approaches, i.e., AONT-RS and CAONT-RS, as example cases to deploy our scheme. Accordingly, we propose their network coding-based enhancements, namely NAONT-RS and NCAONT-RS. We implement a prototype cloud-of-clouds system to verify the efficiency of our proposal. We deploy the prototype on Microsoft Azure and conduct extensive experiments with real-world traces. The experimental results show that NAONT-RS and NCAONT-RS can reduce the time of data storage process by up to 50% and improve the throughput by up to 110% compared with their original versions, i.e., AONT-RS and CAONT-RS.
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