Lengdong Wu

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This paper proposes a new formula protocol for distributed concurrency control, and specifies a staged grid architecture for highly scalable database management systems. The paper also describes novel implementation techniques of Rubato DB based on the proposed protocol and architecture. We have conducted extensive experiments which clearly show that Rubato(More)
Today, data is flowing into various organizations at an unprecedented scale. The ability to scale out for processing an enhanced workload has become an important factor for the proliferation and popularization of database systems. Big data applications demand and consequently lead to the developments of diverse large-scale data management systems in(More)
—Big data applications demand and consequently lead to developments of large-scale data management systems, which provide high scalability by partitioning data across multiple servers. Since conventional transactional access is quite expensive, many real world large-scale distributed systems eschew transactional functionality and adopt semantics of atomic(More)
In the medical field, we are amassing phenomenal amounts of data. This data is imperative in discovering patterns and trends to help improve healthcare. Yet the researchers cannot rejoice as the data cannot be easily shared, because health data custodians have the understandable ethical and legal responsibility to maintain the privacy of individuals. Many(More)
We propose to demonstrate Rubato DB, a highly scalable NewSQL system, supporting various consistency levels from ACID to BASE for OLTP and big data applications. Rubato DB employs the staged grid architecture with a novel formula based protocol for distributed concurrency control. Our demonstration will present Rubato DB as one NewSQL database management(More)
Today, data is flowing into various organizations at an unprecedented scale in the world. The ability to scale out for processing an enhanced workload has become an important factor for the proliferation and popularization of database systems. Big data applications demand and consequently lead to developments of diverse large-scale data management systems(More)
In the medical field, we are amassing phenomenal amounts of data. Because of understandable ethical and legal responsibility to maintain the privacy, many techniques of anonymization have been proposed to provide means of data publishing without jeopardizing privacy. The strictness of the techniques is putting in question the utility of the health data(More)
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