Improving Resource Utilization, Scalability, and Availability in Replication Systems Using Object Ownership Distribution

Mostafa, Almetwally M.; Youssef, Ahmed E.

doi:10.1007/s13369-014-1375-1

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…The disadvantage of active replication is that in practice most of the real world servers are nondeterministic. In passive replication [8][9][10][11][12][13][14], there is one replica, the primary, which executes the client requests and propagates the new states to all other replicas (backup servers). Then, the backups apply updates in the same order sent by the primary.…”

Section: Related Workmentioning

confidence: 99%

“…Their main objective is to improve replication cell performance by distributing consistency management responsibilities among servers. These approaches include different variants of Paxos such as Multi-Paxos [16 and 17], Fast Paxos [27], Mencius [28], generalized Paxos [29], EPaxos [30], Object Ownership Distribution (OOD) [13], and chain replication [32][33][34][35][36].…”

Section: Related Workmentioning

confidence: 99%

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Bidirectional Chain Replication for Higher Throughput Provision

2019

KSII TIIS

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Provision of higher throughput without sacrificing consistency guarantees in replication systems is a critical problem. In this paper, we propose a novel approach called Bidirectional Chain Replication (BCR) to improve throughput in traditional Chain Replication (CR) through better utilization of computing and communication resources of the chain. Unlike CR where the whole replicated data store is treated as a single unit, in BCR the replicated shared data at each server in the chain is split into two disjoint Logical Partitions (LP 1 , LP 2). This forms two chains running concurrently on the same hardware in two opposite directions; the first chain (CR 1) exclusively manipulates data objects in LP 1 , while the second chain (CR 2) exclusively manipulates data objects in LP 2 , therefore, conflict is avoided and concurrency is guaranteed. The simultaneous employment of these two chains results in better utilization of hardware in the sense that the two chains can evenly share the workload, hence, throughput can be improved without sacrificing consistency. Experimental results showed an improvement of approximately 85% in throughput of BCR over CR.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Bidirectional Chain Replication for Higher Throughput Provision

2019

KSII TIIS

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“…Ravimaran et al [31] have discussed about a technique called Integrated Obj_FedRep (IOFR) model, which takes care of replication, and also the model finally reduces network traffic and provides better bandwidth utilization. Mostafa et al [1] in their paper have discussed about the importance of primary backup replication (PBR) and the consistency of the replication for the whole object store. In addition, they also discussed that the data availability and data accessibility are completely lost in case of primary failure.…”

Section: Frequent Itemset Schemesmentioning

confidence: 99%

“…Cloud computing has become the most attractive field in industry and in research. The requirements for cloud computing have increased in recent days due to the utilization of the software and the hardware with less investment [1,2]. As the number of files stored in the cloud increases with requirements reaching exabytes, finding the data relevant to user's requirement in optimum time poses as the greatest challenge.…”

Section: Introductionmentioning

confidence: 99%

“…The update of metadata is taken care by local bloom filter. The architecture handles these by: (1) proposing a protocol for creating the metadata and also to find the replica location of the metadata using GBF, (2) proposing a protocol for update mechanism of dynamic metadata using local bloom filter (LBF) and (3) analyzing the metadata files using bloomier matrix filter (BMF). The use of bloom filters in the 'MaaS' service makes the search and updates more effective thereby reducing both the time and network traffic.…”

Section: Introductionmentioning

confidence: 99%

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‘MaaS’: Fast Retrieval of Data in Cloud Using Metadata as a Service

Anitha

Mukherjee

2015

Arab J Sci Eng

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In cloud era as the data stored is enormous, efficient retrieval of data with reduced latency plays a major role. In cloud, owing to the size of the stored data and lack of locality information among the stored files, metadata is a suitable method of keeping track of the storage. This paper describes a novel framework for efficient retrieval of data from the cloud data servers using metadata with less amount of time. Performance of queries due to availability of files for query processing can be greatly improved by the efficient use of metadata and its analysis thereof. Hence this paper proposes a generic approach of using metadata in cloud, named 'MaaS-Metadata as a Service.' The proposed approach has exploited various methodologies in reducing the latency during data retrieval. This paper investigates the issues on creation of metadata, metadata management and analysis of metadata in a cloud environment for fast retrieval of data. Cloud bloom filter, a probabilistic data structure used for efficient retrieval of metadata is stored across various metadata servers dispersed geographically. We have implemented the model in a cloud environment, and the experimental results show that methodology used is efficient in increasing the throughput and also by handling large number of queries efficiently with reduced latency. The efficacy of the approach is tested through experimental studies using KDD Cup 2003 dataset. In the experimental results, proposed 'MaaS' has outperformed other existing methods.

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