“CHARON: A Secure Cloud-of-Clouds System for Storing and Sharing Big Data”

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|type=article
|type=article
|title=CHARON: A Secure Cloud-of-Clouds System for Storing and Sharing Big Data
|title=CHARON: A Secure Cloud-of-Clouds System for Storing and Sharing Big Data
-
|author=Ricardo Mendes, Tiago Oliveira, Vinicius Vielmo Cogo, Nuno Neves, Alysson Bessani,  
+
|author=Ricardo Mendes, Tiago Oliveira, Vinicius Vielmo Cogo, Nuno Neves, Alysson Bessani,
-
|Project=Project:SUPERCLOUD, Project:BioBankCloud, Project:DiSIEM, Project:IRCoC,  
+
|Project=Project:SUPERCLOUD, Project:BioBankCloud, Project:DiSIEM, Project:IRCoC,
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT)
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT)
|month=may
|month=may
|year=2019
|year=2019
|abstract=We present CHARON, a cloud-backed storage system capable of storing and sharing big data in a secure, reliable, and efficient way using multiple cloud providers and storage repositories to comply with the legal requirements of sensitive personal data. CHARON implements three distinguishing features: (1) it does not require trust on any single entity, (2) it does not require any client-managed server, and (3) it efficiently deals with large files over a set of geo-dispersed storage services. Besides that, we developed a novel Byzantine-resilient data-centric leasing protocol to avoid write-write conflicts between clients accessing shared repositories. We evaluate CHARON using micro and application-based benchmarks simulating representative workflows from bioinformatics, a prominent big data domain. The results show that our unique design is not only feasible but also presents an end-to-end performance of up to 2.5x better than other cloud-backed solutions.
|abstract=We present CHARON, a cloud-backed storage system capable of storing and sharing big data in a secure, reliable, and efficient way using multiple cloud providers and storage repositories to comply with the legal requirements of sensitive personal data. CHARON implements three distinguishing features: (1) it does not require trust on any single entity, (2) it does not require any client-managed server, and (3) it efficiently deals with large files over a set of geo-dispersed storage services. Besides that, we developed a novel Byzantine-resilient data-centric leasing protocol to avoid write-write conflicts between clients accessing shared repositories. We evaluate CHARON using micro and application-based benchmarks simulating representative workflows from bioinformatics, a prominent big data domain. The results show that our unique design is not only feasible but also presents an end-to-end performance of up to 2.5x better than other cloud-backed solutions.
-
|journal= IEEE Transactions on Cloud Computing
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|journal=IEEE Transactions on Cloud Computing
|note=10.1109/TCC.2019.2916856
|note=10.1109/TCC.2019.2916856
|volume=Early Access
|volume=Early Access
|pages=1--12
|pages=1--12
 +
|url=https://ieeexplore.ieee.org/document/8713877
}}
}}

Revision as of 13:58, 15 July 2019

Ricardo Mendes, Tiago Oliveira, Vinicius Vielmo Cogo, Nuno Neves, Alysson Bessani

IEEE Transactions on Cloud Computing, vol. Early Access, pp. 1–12, May 2019.

10.1109/TCC.2019.2916856.
Abstract: We present CHARON, a cloud-backed storage system capable of storing and sharing big data in a secure, reliable, and efficient way using multiple cloud providers and storage repositories to comply with the legal requirements of sensitive personal data. CHARON implements three distinguishing features: (1) it does not require trust on any single entity, (2) it does not require any client-managed server, and (3) it efficiently deals with large files over a set of geo-dispersed storage services. Besides that, we developed a novel Byzantine-resilient data-centric leasing protocol to avoid write-write conflicts between clients accessing shared repositories. We evaluate CHARON using micro and application-based benchmarks simulating representative workflows from bioinformatics, a prominent big data domain. The results show that our unique design is not only feasible but also presents an end-to-end performance of up to 2.5x better than other cloud-backed solutions.

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Project(s): Project:SUPERCLOUD, Project:BioBankCloud, Project:DiSIEM, Project:IRCoC

Research line(s): Fault and Intrusion Tolerance in Open Distributed Systems (FIT)

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