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'MaaS': fast retrieval of E-file in cloud using metadata as a service

机译:“Maas”:使用元数据作为服务的云中的电子文件快速检索

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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 on 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.
机译:在存储的数据庞大时,在云时代,有效地检索具有减少的延迟的数据扮演主要作用。在云中,由于存储的数据的大小和存储的文件中的位置信息缺少,元数据是保持存储跟踪的合适方法。本文介绍了一种新颖的框架,用于使用少量时间的元数据有效地从云数据服务器中检索数据。由于高效使用元数据及其分析,可以大大提高由于查询处理的文件的可用性而验证的性能。因此,本文提出了一种在云中使用元数据的通用方法,名为“MaaS-Metadata作为服务”。该方法利用各种方法来减少数据检索期间的延迟。本文调查了云环境中创建元数据,元数据管理和元数据分析的问题,以便快速检索数据。云绽放过滤器,用于有效检索元数据的概率数据结构存储在地理上分散的各种元数据服务器上。我们在云环境中实现了模型,实验结果表明,使用方法是有效地增加吞吐量,并且还通过减少延迟减少处理大量查询。使用KDD CUP 2003数据集进行实验研究测试该方法的功效。在实验结果中,提出的“MAA”已经表现出其他现有方法。

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