DCaaS: Data Consistency as a Service for Managing Data Uncertainty on the Clouds
Islam Elgedawy

TL;DR
This paper introduces DCaaS, a platform service that manages data uncertainty in cloud environments by avoiding locking techniques, thus improving response times and ensuring data correctness across distributed datacenters.
Contribution
It proposes a quota-based approach for data consistency management in clouds and encapsulates it within a new platform service, DCaaS, enhancing cloud portability and performance.
Findings
DCaaS improves response times over classical locking methods.
The quota-based approach guarantees global data correctness.
DCaaS facilitates cloud portability for SaaS applications.
Abstract
Ensuring data correctness over partitioned distributed database systems is a classical problem. Classical solutions proposed to solve this problem are mainly adopting locking or blocking techniques. These techniques are not suitable for cloud environments as they produce terrible response times; due to the long latency and faultiness of wide area network connections among cloud datacenters. One way to improve performance is to restrict access of users-bases to specific datacenters and avoid data sharing between datacenters. However, conflicts might appear when data is replicated between datacenters; nevertheless change propagation timeliness is not guaranteed. Such problems created data uncertainty on cloud environments. Managing data uncertainty is one of the main obstacles for supporting global distributed transactions on the clouds. To overcome this problem, this paper proposes an…
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