2026-04-30T22:19:42Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/2932 2022-03-24T23:11:47Z 1582963342780:1596102355557 user-uit

Automatic Adjustment of Consistency Level by Predicting Staleness Rate for Distributed Key-Value Storage System Thazin Nwe Junya Nakamura Ei Chaw Htoon Tin Tin Yee Nowadays, Distributed Key-Value storage is extremely useful in almost every large system. Most of the data management systems use Distributed Key-Value database in order to manage and process large volume of data in real time. In such databases, Apache Cassandra is a peerto- peer architecture which any user can connect to any node in any data center and can read and write data anywhere. Most of these systems usually select a fixed number of replicas of read/write requests in Key-Value storage. When the more replicas a read request chooses, it may increase the response time and reduce the system performance. Consistency in Key-Value data storage systems requires any read operation to return the most recent written version of the content. The system provides transaction services which provide NoSQL databases with enhanced consistency by varying the read and write quorum size. The proposed approach tends to automatically select the minimum number of consistent replicas by predicting the staleness rate on adjusting the consistency level. 2018-11-02 http://hdl.handle.net/20.500.12678/0000002932 https://meral.edu.mm/records/2932