AutoGR: Automated Geo-Replication with Fast System Performance and Preserved Application Semantics Jiawei Wang1, Cheng Li1,4, Kai Ma1, Jingze Huo1, Feng Yan2, Xinyu Feng3, Yinlong Xu1,4 1University of Science and Technology of China 2University of Nevada, Reno 3State Key Laboratory for Novel Software Technology, Nanjing University 4Anhui Province Key Laboratory of High Performance Computing
[email protected],{chengli7,ylxu}@ustc.edu.cn,{ksqsf,jzfire}@mail.ustc.edu.cn,
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[email protected] ABSTRACT static runtime Geo-replication is essential for providing low latency response AP AP and quality Internet services. However, designing fast and correct Analyzer Code App ( Rigi ) geo-replicated services is challenging due to the complex trade-off US EU US EU between performance and consistency semantics in optimizing the expensive cross-site coordination. State-of-the-art solutions rely Restrictions on programmers to derive sufficient application-specific invariants Cross-site Causally Consistent Schema Coordination and code specifications, which is both time-consuming and error- Database Service Geo-Replicated Store prone. In this paper, we propose an end-to-end geo-replication APP Servers deployment framework AutoGR (AUTOmated Geo-Replication) to free programmers from such label-intensive tasks. AutoGR en- Figure 1: An overview of the proposed end-to-end AutoGR ables the geo-replication features for non-replicated, serializable solution. AP, US, and EU stand for data centers in Singapore, applications in an automated way with optimized performance and Oregon, and Frankfurt, respectively. The runtime library is correct application semantics. Driven by a novel static analyzer Rigi, co-located with Server, omitted from the graph.