Harnessing RAID mechanism for enhancement of data storage and security on cloud

Sahana, Sudipta; Bose, Rajesh; Sarddar, Debabrata

doi:10.1186/s40552-016-0024-5

Cited by 8 publications

(3 citation statements)

References 16 publications

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“…Incidentally, the aspect of data retrieval also begins to take on a greater significance when taken in context of many millions of users who rely on Cloud Computing to store data. Enterprises and organizations prefer to go the Cloud Computing route because of convenience and ease in not only storing data, but also retrieval of such at a later date [10]. As noted and documented in research conducted [11], for Cloud Computing data centers to conserve power at every possible stage, power usage and heat sensitivity issues need to be addressed.…”

Section: Related Workmentioning

confidence: 99%

Advancing Cloud Network Management with Smart Monitoring Technique

Sahana*,

Bose,

Sarddar

2020

IJRTE

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The proliferation of Cloud Computing has opened new and attractive offerings for consumers. Cloud Service Providers promote and market packages of cloud computing services that cater to diverse opportunities and user applications. While this has obvious advantages, there are certain factors that are a cause for concern. Monitoring the underlying infrastructure that supports the entire fabric of cloud computing is an aspect that requires a great deal of attention. The aspect of monitoring takes on a great deal of significance when performance and robustness of cloud service on offer is taken into consideration. Although research has been conducted into various cloud computing monitoring techniques, there is scope and room yet for an integrated cloud monitoring solution that can fulfill the requirements of cloud administrators to ensure optimal performance of the underlying infrastructure of a cloud computing network. In this paper, we propose a unified monitoring model that is essentially a composite framework involving hardware and network layers. Studies conducted during our experiments suggest that our unified cloud monitoring approach can significantly aid in reducing overall carbon emissions while helping meeting compliance and audit norms by ensuring that the underlying cloud infrastructure is monitored closely

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Section: Related Workmentioning

confidence: 99%

Advancing Cloud Network Management with Smart Monitoring Technique

Sahana*,

Bose,

Sarddar

2020

IJRTE

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“…Hansen and Archibald proposed a solution combining local and cloud storage in a RAID‐like configuration to achieve high data reliability and increase the amount of storage and access speed . Sahana et al introduced a technique of data storage using file type classification and RAID to improve reliability and availability of cloud storage systems . Liu and Xing developed a two‐level hierarchical methodology combining continuous‐time Markov chains and combinatorial multivalued decision diagrams (MDDs) to assess reliability of cloud‐RAID 5 and 6 storage systems with heterogeneous disks from different providers, but without considering the IPC .…”

Section: Introductionmentioning

confidence: 99%

“…13 Sahana et al introduced a technique of data storage using file type classification and RAID to improve reliability and availability of cloud storage systems. 14 Liu and Xing developed a two-level hierarchical methodology combining continuous-time Markov chains and combinatorial multivalued decision diagrams (MDDs) to assess reliability of cloud-RAID 5 and 6 storage systems with heterogeneous disks from different providers, but without considering the IPC. 15,16 In recent works, 17,18 the effects of the IPC were addressed in the reliability analysis of binary-state cloud storage systems, where the cloud-RAID system and its disks are assumed to be either operational or failed.…”

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confidence: 99%

Fault‐level coverage analysis of multistate cloud‐RAID storage systems

Mandava

Xing

Wang

2019

Engineering Reports

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In this paper, a multistate cloud‐RAID (redundant array of independent disks) storage system subject to fault‐level coverage (FLC) is modeled and analyzed. Most of the existing works on reliability analysis of cloud‐RAID systems have either assumed binary‐state for storage disks or failed to consider imperfect fault coverage, an inherent behavior of fault‐tolerant systems. This work advances the state of the art by proposing a combinatorial method based on multivalued decision diagrams for analyzing reliability of a multistate cloud‐RAID system with FLC. The FLC is one common type of imperfect fault coverage behaviors, where the system fault recovery capability is dependent on the number of disk faults happening within a certain recovery window. Effects of the functional dependence behavior between the RAID controller and disks are addressed. The method is illustrated through a detailed analysis of an example cloud‐RAID 5 storage system. Numerical results are provided to show the impact of different design parameters on system performance. These results also demonstrate that failure to consider FLC leads to inaccurate system state probabilities, further misleading system design activities based on these probabilities such as maintenance and optimization.

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Application Safety and Service Vulnerability in Cloud Network

Sahana¹,

Sarddar

2019

Security Designs for the Cloud, Iot, and Social Networking

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Harnessing RAID mechanism for enhancement of data storage and security on cloud

Cited by 8 publications

References 16 publications

Advancing Cloud Network Management with Smart Monitoring Technique

Advancing Cloud Network Management with Smart Monitoring Technique

Fault‐level coverage analysis of multistate cloud‐RAID storage systems

Application Safety and Service Vulnerability in Cloud Network

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