In this paper we define the overflow problem of a network coding storage system in which the encoding parameter and the storage parameter are mismatched. Through analyses and experiments, we first show the impacts of the overflow problem in a network coding scheme, which not only waste storage spaces, but also degrade coding efficiency. To avoid the overflow problem, we then develop the network coding based secure storage (NCSS) scheme. Thanks to considering both security and storage requirements in encoding procedures and distributed architectures, the NCSS can improve the performance of a cloud storage system from both the aspects of storage cost and coding processing time. We analyze the maximum allowable stored encoded data under the perfect secrecy criterion, and provide the design guidelines for the secure cloud storage system to enhance coding efficiency and achieve the minimal storage cost.
Network coding can improve the efficiency of data recovery process when storage nodes fail in distributed storage systems. It was proved that the data recovery problem of distributed storage systems is equivalent to the multicasting problem of network routing @cite_2 . The authors of @cite_19 designed a cooperative network coding recovery mechanism for multiple node failures. A proxy-based multiple cloud storage system with the feature of fault tolerance was built based on the network coding storage scheme @cite_7 . A network coding method called Regenerating Code was proposed to improve the repair process of distributed storage systems @cite_17 . Different from erasure coding, the repaired data fragments are mixed in intermediate nodes, thereby reducing the repair bandwidth. The authors of @cite_14 applied network coding to optimize the reliability performance of frequently accessed data in cloud storage systems.
@cite_14 @cite_7 @cite_19 @cite_2 @cite_17
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In order to provide high data reliability, distributed storage systems disperse data with redundancy to multiple storage nodes. Regenerating codes is a new class of erasure codes to introduce redundancy for the purpose of improving the data repair performance in distributed storage. Most of the studies on regenerating codes focus on the single-failure recovery, but it is not uncommon to see two or more node failures at the same time in large storage networks. To exploit the opportunity of repairing multiple failed nodes simultaneously, a cooperative repair mechanism, in the sense that the nodes to be repaired can exchange data among themselves, is investigated. A lower bound on the repair-bandwidth for cooperative repair is derived and a construction of a family of exact cooperative regenerating codes matching this lower bound is presented. To provide fault tolerance for cloud storage, recent studies propose to stripe data across multiple cloud vendors. However, if a cloud suffers from a permanent failure and loses all its data, we need to repair the lost data with the help of the other surviving clouds to preserve data redundancy. We present a proxy-based storage system for fault-tolerant multiple-cloud storage called NCCloud, which achieves cost-effective repair for a permanent single-cloud failure. NCCloud is built on top of a network-coding-based storage scheme called the functional minimum-storage regenerating (FMSR) codes, which maintain the same fault tolerance and data redundancy as in traditional erasure codes (e.g., RAID-6), but use less repair traffic and, hence, incur less monetary cost due to data transfer. One key design feature of our FMSR codes is that we relax the encoding requirement of storage nodes during repair, while preserving the benefits of network coding in repair. We implement a proof-of-concept prototype of NCCloud and deploy it atop both local and commercial clouds. We validate that FMSR codes provide significant monetary cost savings in repair over RAID-6 codes, while having comparable response time performance in normal cloud storage operations such as upload download. Distributed storage systems can store data with erasure coding to maintain data availability with low storage redundancy. One class of erasure coding is based on regenerating codes , which provably minimize the amount of data transferred for failure repair and realize the optimal tradeoff between the storage redundancy and the amount of traffic transferred for repair. Typical regenerating codes often require surviving storage nodes to encode their stored data for repair. In this paper, we study a framework called proxy-assisted regeneration, which offloads the repair process to a centralized proxy. We extend the previous applied work on proxy-assisted regeneration by providing theoretical validation. Specifically, we study a special class of regenerating codes called proxy-assisted minimum storage regenerating (PMSR) codes, which enable uncoded repair without the need of encoding in surviving nodes, while preserving the minimum storage redundancy and minimum amount of traffic transferred for repair. We formally prove the existence of PMSR codes for two configurations: 1) repairing single-node failures under double fault tolerance and 2) repairing double-node failures under triple fault tolerance. We also provide a semi-deterministic PMSR code construction for repairing single-node failures under double fault tolerance. Network coding is an important cloud storage technique, which can recover data with small repair bandwidth and high reliability compared to the existing erasure coding and replication methods. However, regardless of which data recovery technique is used, the repaired data in a geographically distributed cloud storage system are easy to be eavesdropped at the transmission link between the local datacenter and its remote backup site. This kind of network security issue is called link eavesdropping in this paper. For a network coded cloud storage system, we propose a systematic design methodology to determine the important data recovery system parameters for any specified security level. Through analysis, we present the performance curves to relate the remote repair bandwidth and the number of coded data fragments. Consequently, all the important system parameters of a network coded data recovery system, including the number of storage nodes and the link capacity between the datacenter and the backup site, can be precisely designed for satisfying different security level requirements.