Consistent hasing has played a fundamental role as a data router and a load balancer in various fields, such as distributed database, cloud infrastructure, and peer-to-peer network. However, the existing consistent hashing schemes can't meet the requirements simultaneously, including full consistency, scalability, small memory footprint, low update time and low query complexity. Thus, We propose DxHash, a scalable consistent hashing algorithm based on the pseudo-random sequence. For the scenario of distributed storage, there are two optimizations based on DXHash are proposed. First, the Weighted DxHash can adjust the workloads on arbitrary nodes. Second, the Asymmetric Replica Strategy (ARS) is combining the replica strategy in distributed storage with the scaleup process to improve the availability of the system and reduce the remapping rate. The evaluation indicates that compared with the state-of-art works, DxHash achieves significant improvements on the 5 requirements. Even with 50% failure ratio, DxHash still can complete 16.5 million queries per second. What's more, the two optimizations both achieve their own results.