Distributed audit causal consistency model based on biased stability

Abstract

In the distributed storage, causal consistency is favored due to the best trade-off between ease of programming and performance.To address the problem of vector-dependent tracking loss of throughput in existing causal consistency results, a distributed audit causal consistency model based on biased stability was proposed.Combined vector timestamps were used instead of full vector timestamps in query operations to reduce system management and communication overhead.Meanwhile, the causal auditing was introduced with the help of distributed associative arrays, and data dependency was refined by partitioned cooperative auditing to reduce the number of false dependency entries.Theoretical analysis and simulation results show that proposed model improves throughput by 48.26% and reduces update response latency by 16.25%.

Keywords

• data consistency;causal consistency;distributed storage;bias stability;causal audit