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Multi-level inline data deduplication

A data-level technology, applied in the direction of electrical digital data processing, special data processing applications, digital data information retrieval, etc., can solve the problems of reducing deduplication throughput, auxiliary storage disk bottlenecks, etc.

Inactive Publication Date: 2015-07-29
INDIAN INSTITUTE OF TECHNOLOGYKHARAGPUR
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since deduplication involves processing large datasets, secondary storage disk bottlenecks that can reduce deduplication throughput are the main challenge

Method used

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  • Multi-level inline data deduplication
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Embodiment Construction

[0018] In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The exemplary embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that, as generally described herein and illustrated in the drawings, the aspects of the present disclosure can be arranged, substituted, combined, separated and designed in various configurations, all of which are expressly contemplated herein .

[0019] The present disclosure relates generally to methods, apparatus, systems, devices, and / or computer program products related to providing multi-level, inline data deduplication for data center environments, among o...

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Abstract

Technologies are presented for data deduplication that operates at relatively high throughput and with relatively less storage space than conventional techniques. Building upon content-dependent chunking (CDC) using Rabin fingerprints, data may be fingerprinted and stored in variable-size chunks. In some examples, data may be chunked on multiple levels, for example, two levels, variable size large chunks in the first level and fixed-size sub-chunks in the second level, in order to prevent sub-chunks common to two or more data chunks from not being deduplicated. For example, at a first level, a CDC algorithm may be employed to fingerprint and chunk data in content-dependent sizes (variable sizes), and at a second level the CDC chunks may be sliced into small fixed-size chunks. The sliced CDC chunks may then be used for deduplication.

Description

Background technique [0001] Unless otherwise indicated herein, the materials described herein are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section. [0002] With the development of network and data storage technologies, more and more computing services are provided to users or customers through cloud-based data centers, which can realize leased access to various levels of computing resources. Data centers can provide a series of system configuration and operation solutions for individuals and organizations. Although data centers are equipped to handle data storage and processing on a very large scale, data storage still incurs resources, bandwidth, speed, and financial cost of equipment. Another aspect of data center operations is the deduplication of inter-user data (eg, applications, configuration data, and consumable data). [0003] Fixed-size chunking and content-dependent chunking (CDC) based on Rabin fing...

Claims

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Application Information

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IPC IPC(8): G06F17/00
CPCG06F3/0608G06F17/30159G06F3/0641G06F3/0613G06F16/1752
Inventor R·S·查克拉博蒂B·K·迪狄
Owner INDIAN INSTITUTE OF TECHNOLOGYKHARAGPUR
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