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Replication and erasure codes are two popular schemes to provide fault tolerance in distributed storage systems. However, they both face some challenges when used in cloud storage. As the scale of data increases and failure becomes common in data centers, replication scheme suffers from high storage cost while erasure codes suffer from performance degradation and network bandwidth cost particularly...
Erasure codes are widely deployed in storage systems and the encoding/decoding process is a common operation in erasure-coded systems. Parity-check matrix method is a general method employed in erasure codes to conduct encoding/decoding process. However, the process is serial and generates high computational cost in dealing with matrix operations, and hence, causes low encoding/decoding performance...
It is indispensable to speed up a reconstruction process in erasure-coded storage clusters, because a fast data recovery helps to shorten the vulnerability window while improving storage system reliability. To address double- and multiple-node failures, this paper proposes a cooperative reconstruction pattern - CoRec - to minimize reconstruction traffic. CoRec not only enables all rebuilding nodes...
As hard disk failure rates are rarely improved and the reconstruction time for TB-level disks typically amounts to days, multiple concurrent disk/storage node failures in datacenter storage systems become common and frequent. As a result, the erasure coding schemes used in datacenters must meet the critical requirements of high fault tolerance, high storage efficiency, and fast fault recovery. In...
In today's large data centers, hundreds to thousands of nodes are deployed as storage clusters to provide cloud and big data storage service, where failures are not rare. Therefore, efficient data redundancy technologies are needed to ensure data availability and reliability. Compared to traditional technology based on replication, erasure codes which tolerate multiple failures provide availability...
To reduce the probability of data unavailability, it is extremely important to quickly recover failed data in a (k+r, k) erasure-coded storage cluster. In practice, storage nodes in a large-scale storage system have various network bandwidths and I/O capabilities, therefore, the heterogeneity of storage systems increases along with the growing scale. Both traditional recovery scheme and Fastest recovery...
Storage systems become heterogeneous with the scale increasing, because they consist of a lot of different types of servers with various I/O capacities. Slow servers usually lead to long response time, raising a negative impact on the Quality of Service (QoS) of storage. In this paper, we exploit the heterogeneity of the storage system to shorten the user access latency. We propose a QoS-Aware Read...
Nowadays, erasure codes have been widely used in data storage to achieve high fault-tolerance. However, compared with replica-based storage, erasure-coded system may suffer significant performance overhead in encoding, decoding and updating. Traditional updating schemes(e.g. DUM and PUM) use an individual manager node to accomplish the updating. In this paper, we propose two partial-updating schemes...
Decentralized, cooperative and large-scale distributed storage systems that consist of a cluster of storage nodes attached with local disks can deliver high resource utilization, high availability and easy scalability. Therefore they become a cost-effective solution. High availability with node failures, strong data consistency, flexible expandability and high I/O throughput are still important challenges...
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