Data Consistency in Multi-Cloud Storage Systems With Passive Servers and Non-Communicating Clients

Abstract

Multi-cloud storage systems are becoming more popular due to the ever-expanding amount of consumer data. This growth is accompanied by increasing concerns regarding security, privacy, and reliability of cloud storage solutions. Ensuring data consistency in such systems is especially challenging due to their architecture and characteristics. Specifically, passive cloud storage cannot run coordination software, and clients cannot communicate directly to reach consensus. Furthermore, the atomicity of operations is not always guaranteed by the clouds' public APIs. In this paper, we formally define data consistency in multi-cloud storage systems, identify how they can be violated, and introduce a new method that provably maintains the data consistency in these systems. The implementation and experiments show that the proposed method can maintain data consistency with a certain delay in data uploading and that it is scalable with respect to the number of used clouds as well as the number of users. Integrating this method into multi-cloud storage systems will enhance their usability and reliability.

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“…Multiple data objects potentially employ the same data fragment and third-parties data fragments may be outside one's control. Data consistency is an important factor in ensuring that updates and deletions are properly reflected across the multi-cloud [13]. Dynamic systems are necessary to upkeep countless data fragments in a distributed environment [16].…”

Predictive cloud control for nonlinear multiagent systems based on extended state observer and quantizers

“…To address the computational issues, researchers have been presented cloud control systems based on cloud computing and traditional network control frameworks. 11 In Reference 12, the predictive cloud control scheme has been presented through cloud computing. Cloud control systems with attacks have been analyzed in Reference 13.…”

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