A5091021480- Cloud Computing and Resource Management
- Distributed systems and fault tolerance
- Advanced Data Storage Technologies
- Privacy-Preserving Technologies in Data
- Advanced Database Systems and Queries
- Mobile Crowdsensing and Crowdsourcing
- Stochastic Gradient Optimization Techniques
Antea Group (France)
2023
We have designed and developed OceanBase, a distributed relational database system from the very basics for decade. Being scale-out multi-tenant system, OceanBase is cross-region fault tolerant, which based on shared-nothing architecture. Besides sharing many similar goals with alternative DBMS, such as horizontal scalability, fault-tolerance, etc., our design has been driven by demands of typical RDBMS compatibility well both on-premise off-premise deployments. fulfilled its goal. It...
In the ongoing evolution of OceanBase database system, it is essential to enhance its adaptability small-scale enterprises. The system has demonstrated stability and effectiveness within Ant Group other commercial organizations, besides through TPC-C TPC-H tests. this paper, we have designed a stand-alone distributed integrated architecture named Paetica address overhead caused by components in mode, with respect system. enables adaptive configuration that allows support both serial parallel...
With the rapid development of distributed transactional databases in recent years, there is an urgent need for fair performance evaluation and comparison. Though are various open-source benchmarks built databases, it lack a comprehensive study about applicability databases. This paper presents review state-of-art with respect to We first summarize representative architectures then provide overview chock points Then, we classify classic based on their characteristics design purposes. Finally,...
Distributed relational database management systems (abbr. DDBMSs) for online transaction processing OLTP) have been gradually adopted in production environments. With many relevant products vying the markets, an unbiased benchmark is urgently needed to promote development of transactional DDBMSs. Current benchmarks OLTP applications not taken challenges encountered during designs and implementations a DDBMS into consideration, which expects provide high elasticity availability as well...
This paper proposes a federated, fair, and fast k-means algorithm (F3KM) to solve the fair clustering problem efficiently in scenarios where data cannot be shared among different parties. The proposed decomposes into multiple subproblems assigns each subproblem client for local computation. Our allows possess sensitive attributes (or have no attributes). We propose an in-processing method that employs alternating direction of multipliers (ADMM) subproblem. During procedure solving...