Conference Proceedings

Distributed Data Load Balancing for Scalable Key-Value Cache Systems

S Chen, X Zhou, G Zhou, RO Sinnott

Communications in Computer and Information Science | SpringerLink | Published : 2018

Abstract

© 2018, Springer Nature Singapore Pte Ltd. In recent years, in-memory key-value cache systems have become increasingly popular in tackling real-time and interactive data processing tasks. Caching systems are often used to help with the temporary storage and processing of data. Due to skewed and dynamic workload patterns, e.g. data increase/decrease or request changes in read/write ratio, it can cause load imbalance and degrade performance of caching systems. Migrating data is often essential for balancing load in distributed storage systems. However, it can be difficult to determine when to move data, where to move data, and how much data to move. This depends on the resources required, e.g...

View full abstract

Grants

Awarded by National Basic Research 973 Program of China


Awarded by National Natural Science Foundation of China (NSFC)


Awarded by Natural Science Foundation of Jiangsu Province


Awarded by Nanjing University of Posts and Telecommunications Scientific Research Fund


Funding Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments. This work is partially sponsored by the National Basic Research 973 Program of China (No. 2015CB352403), the National Natural Science Foundation of China (NSFC) (No. 61402014, No. 63100240, No. 61572263), the Natural Science Foundation of Jiangsu Province (BK20151511) and Nanjing University of Posts and Telecommunications Scientific Research Fund (NY215115).