Proactive replica checking to assure reliability of data in cloud storage with minimum replication
01 Nov 2017-Vol. 263, Iss: 4, pp 042063
TL;DR: This paper presents a cost-efficient data reliability mechanism named PRCR to cut back the cloud storage consumption and shows that when resembled to the standard three-replica approach, PRCR will scale back to consume only a simple fraction of the cloud Storage from one-third of the storage, thence considerably minimizing the cloudstorage price.
Abstract: The two major issues for cloud storage systems are data reliability and storage costs. For data reliability protection, multi-replica replication strategy which is used mostly in current clouds acquires huge storage consumption, leading to a large storage cost for applications within the loud specifically. This paper presents a cost-efficient data reliability mechanism named PRCR to cut back the cloud storage consumption. PRCR ensures data reliability of large cloud information with the replication that might conjointly function as a price effective benchmark for replication. The duplication shows that when resembled to the standard three-replica approach, PRCR will scale back to consume only a simple fraction of the cloud storage from one-third of the storage, thence considerably minimizing the cloud storage price.
References
More filters
TL;DR: The clouds are clearing the clouds away from the true potential and obstacles posed by this computing capability.
Abstract: Clearing the clouds away from the true potential and obstacles posed by this computing capability.
9,282 citations
TL;DR: This paper explores the design of reliable, redundant disk arrays in the context of a 70-disk strawman array and shows how to balance requirements for high data reliability against the overhead cost of redundant data, on-line spares, and on-site repair personnel in terms of an array′s architecture, its component reliabilities, and its repair policies.
115 citations
10 Aug 2012
90 citations
06 Oct 2008
TL;DR: NDS (Normalcy Deviation Score), a new metric for dynamically quantifying the reliability status of a storage system, is introduced and MinI (Minimum Intersection), a novel recovery scheduling policy that improves reliability by efficiently reconstructing data after a hardware failure is proposed.
Abstract: In this paper, we argue that the reliability of large-scale storage systems can be significantly improved by using better reliability metrics and more efficient policies for recovering from hardware failures. Specifically, we make three main contributions. First, we introduce NDS (Normalcy Deviation Score), a new metric for dynamically quantifying the reliability status of a storage system. Second, we propose MinI (Minimum Intersection), a novel recovery scheduling policy that improves reliability by efficiently reconstructing data after a hardware failure. MinI uses NDS to tradeoff reliability and performance in making its scheduling decisions. Third, we evaluate NDS and MinI for three common data-allocation schemes and a number of different parameters. Our evaluation focuses on a distributed storage system based on erasure codes. We find that MinI improves reliability significantly, as compared to conventional policies.
31 citations
TL;DR: This work presents a solution, referred to as fusion, that uses a combination of erasure codes and selective replication to tolerate f crash faults using just f additional fused backups, and achieves O(n) savings in space over replication.
Abstract: Replication is the prevalent solution to tolerate faults in large data structures hosted on distributed servers. To tolerate f crash faults (dead/unresponsive data structures) among n distinct data structures, replication requires f + 1 replicas of each data structure, resulting in nf additional backups. We present a solution, referred to as fusion that uses a combination of erasure codes and selective replication to tolerate f crash faults using just f additional fused backups. We show that our solution achieves O(n) savings in space over replication. Further, we present a solution to tolerate f Byzantine faults (malicious data structures), that requires only nf + f backups as compared to the 2nf backups required by replication. We explore the theory of fused backups and provide a library of such backups for all the data structures in the Java Collection Framework. The theoretical and experimental evaluation confirms that the fused backups are space-efficient as compared to replication, while they cause very little overhead for normal operation. To illustrate the practical usefulness of fusion, we use fused backups for reliability in Amazon's highly available key-value store, Dynamo. While the current replication-based solution uses 300 backup structures, we present a solution that only requires 120 backup structures. This results in savings in space as well as other resources such as power.
22 citations