Towards a Big Data system disaster recovery in a private cloud
Towards a Big Data system disaster recovery in a private cloud
Disaster Recovery (DR) plays a vital role in restoring the organization’s data in the case of emergency and hazardous accidents. While many papers in security focus on privacy and security technologies, few address the DR process, particularly for a Big Data system. However, all these studies that have investigated DR methods belong to the “single-basket” approach, which means there is only one destination from which to secure the restored data, and mostly use only one type of technology implementation. We propose a “multi-purpose” approach, which allows data to be restored to multiple sites with multiple methods to ensure the organization recovers a very high percentage of data close to 100%, with all sites in London, Southampton and Leeds data recovered. The traditional TCP/IP baseline, snapshot and replication are used with their system design and development explained. We compare performance between different approaches and multi-purpose approach stands out in the event of emergency. Data at all sites in London, Southampton and Leeds can be restored and updated simultaneously. Results show that optimize command can recover 1TB of data within 650 seconds and command for three sites can recover 1 TB of data within 1360 seconds. All data backup and recovery has failure rate of 1.6% and below. All the data centers should adopt multi-purpose approaches to ensure all the data in the Big Data system can be recovered and retrieved without experiencing a prolong downtime and complex recovery processes. We make recommendations for adopting “multi-purpose” approach for data centers, and demonstrate that 100% of data is fully recovered with low execution time at all sites during a hazardous event as described in the paper.
(Due to the copyrights and other requirements, this paper will not be available until the full version is online on ScienceDirect. Sorry for any inconvenience caused)
Disaster Recovery (DR), TCP/IP baseline, snapshot, replication, multi-purpose DR approach, performance measurement
65-82
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
1 December 2015
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Abstract
Disaster Recovery (DR) plays a vital role in restoring the organization’s data in the case of emergency and hazardous accidents. While many papers in security focus on privacy and security technologies, few address the DR process, particularly for a Big Data system. However, all these studies that have investigated DR methods belong to the “single-basket” approach, which means there is only one destination from which to secure the restored data, and mostly use only one type of technology implementation. We propose a “multi-purpose” approach, which allows data to be restored to multiple sites with multiple methods to ensure the organization recovers a very high percentage of data close to 100%, with all sites in London, Southampton and Leeds data recovered. The traditional TCP/IP baseline, snapshot and replication are used with their system design and development explained. We compare performance between different approaches and multi-purpose approach stands out in the event of emergency. Data at all sites in London, Southampton and Leeds can be restored and updated simultaneously. Results show that optimize command can recover 1TB of data within 650 seconds and command for three sites can recover 1 TB of data within 1360 seconds. All data backup and recovery has failure rate of 1.6% and below. All the data centers should adopt multi-purpose approaches to ensure all the data in the Big Data system can be recovered and retrieved without experiencing a prolong downtime and complex recovery processes. We make recommendations for adopting “multi-purpose” approach for data centers, and demonstrate that 100% of data is fully recovered with low execution time at all sites during a hazardous event as described in the paper.
(Due to the copyrights and other requirements, this paper will not be available until the full version is online on ScienceDirect. Sorry for any inconvenience caused)
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VC_Ad_Hoc_Disaster_Recovery.pdf
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More information
Accepted/In Press date: 17 July 2015
Published date: 1 December 2015
Keywords:
Disaster Recovery (DR), TCP/IP baseline, snapshot, replication, multi-purpose DR approach, performance measurement
Organisations:
Electronics & Computer Science, Electronic & Software Systems
Identifiers
Local EPrints ID: 379387
URI: http://eprints.soton.ac.uk/id/eprint/379387
ISSN: 1570-8705
PURE UUID: 5f2c767b-7681-43d5-a024-bfb437ced219
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Date deposited: 19 Jul 2015 20:42
Last modified: 14 Mar 2024 20:40
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Author:
Victor Chang
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