scholarly journals The Case for Object Databases in Cloud Data Management

Author(s):  
Michael Grossniklaus
2014 ◽  
Vol 36 (7) ◽  
pp. 1485-1499 ◽  
Author(s):  
Jie SONG ◽  
Tian-Tian LI ◽  
Zhi-Liang ZHU ◽  
Yu-Bin BAO ◽  
Ge YU

2021 ◽  
Vol 14 (7) ◽  
pp. 1166-1166
Author(s):  
Sujaya Maiyya ◽  
Faisal Nawab ◽  
Divyakant Agrawal ◽  
Amr El Abbadi

This errata article discusses and corrects a minor error in our work published in VLDB 2019. The discrepancy specifically pertains to Algorithms 3 and 4. The algorithms presented in the paper are biased towards a commit decision in a specific failure scenario. We explain the error using an example before correcting the algorithm.


2019 ◽  
pp. 889-902
Author(s):  
Mohammed A. AlZain ◽  
Alice S. Li ◽  
Ben Soh ◽  
Mehedi Masud

One of the main challenges in cloud computing is to build a healthy and efficient storage for securely managing and preserving data. This means a cloud service provider needs to make sure that its clients' outsourced data are stored securely and, data queries and retrievals are executed correctly and privately. On the other hand, it may also mean businesses are willing to outsource their data to a third party only if they trust their data are not accessible and visible to the service provider and other non-authorized parties. However, one of the major obstacles faced here for ensuring data reliability and security is Byzantine faults. While Byzantine fault tolerance (BFT) has received growing attention from the academic research community, the research done is generally from the distributed computing point of view, and hence finds little practical use in cloud computing. To that end, the focus of this paper is to discuss how these faults can be tolerated with the authors' proposed conceptualization of Byzantine data faults and fault-tolerant architecture in cloud data management.


2016 ◽  
pp. 1205-1222
Author(s):  
Mohammed A. AlZain ◽  
Alice S. Li ◽  
Ben Soh ◽  
Eric Pardede

Cloud computing is a phenomenal distributed computing paradigm that provides flexible, low-cost on-demand data management to businesses. However, this so-called outsourcing of computing resources causes business data security and privacy concerns. Although various methods have been proposed to deal with these concerns, none of these relates to multi-clouds. This paper presents a practical data management model in a public and private multi-cloud environment. The proposed model BFT-MCDB incorporates Shamir's Secret Sharing approach and Quantum Byzantine Agreement protocol to improve trustworthiness and security of business data storage, without compromising performance. The performance evaluation is carried out using a cloud computing simulator called CloudSim. The experimental results show significantly better performance in terms of data storage and data retrieval compared to other common cloud cryptographic based models. The performance evaluation based on CloudSim experiments demonstrates the feasibility of the proposed multi-cloud data management model.


2016 ◽  
Vol 7 (3) ◽  
pp. 86-98 ◽  
Author(s):  
Mohammed A. AlZain ◽  
Alice S. Li ◽  
Ben Soh ◽  
Mehedi Masud

One of the main challenges in cloud computing is to build a healthy and efficient storage for securely managing and preserving data. This means a cloud service provider needs to make sure that its clients' outsourced data are stored securely and, data queries and retrievals are executed correctly and privately. On the other hand, it may also mean businesses are willing to outsource their data to a third party only if they trust their data are not accessible and visible to the service provider and other non-authorized parties. However, one of the major obstacles faced here for ensuring data reliability and security is Byzantine faults. While Byzantine fault tolerance (BFT) has received growing attention from the academic research community, the research done is generally from the distributed computing point of view, and hence finds little practical use in cloud computing. To that end, the focus of this paper is to discuss how these faults can be tolerated with the authors' proposed conceptualization of Byzantine data faults and fault-tolerant architecture in cloud data management.


2012 ◽  
Vol 3 (1) ◽  
pp. 17-34 ◽  
Author(s):  
Alexandra Carpen-Amarie ◽  
Alexandru Costan ◽  
Catalin Leordeanu ◽  
Cristina Basescu ◽  
Gabriel Antoniu

Providing an adequate security level in Cloud Environments is currently an extremely active research area. More specifically, malicious behaviors targeting large-scale Cloud data repositories (e.g., Denial of Service attacks) may drastically degrade the overall performance of such systems and cannot be detected by typical authentication mechanisms. This article proposes a generic security management framework allowing providers of Cloud data management systems to define and enforce complex security policies. This security framework is designed to detect and stop a large array of attacks defined through an expressive policy description language and to be easily interfaced with various data management systems. The authors show that they can efficiently protect a data storage system by evaluating the security framework on top of the BlobSeer data management platform. The authors evaluate the benefits of preventing a DoS attack targeted towards BlobSeer through experiments performed on the Grid’5000 testbed.


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