Multi-tenant fair share in NoSQL data stores. Zeng, J. & Plale, B. In 2014 IEEE International Conference on Cluster Computing, CLUSTER 2014, 2014.
doi  abstract   bibtex   
© 2014 IEEE. NoSQL data stores see considerable attention today in big data, cloud hosted environments because of their fault tolerance, distribution and high availability. Shared NoSQL data stores are preferred for their ability to serve multiple tenants simultaneously which can improve resource utilization and lower management costs. Fair share in this setting can be a problem in that NoSQL data stores can be weak in preventing interference between tenants. We propose a methodology for multi-tenant fair share in a NoSQL store, in particular Cassandra. The approach uses an extended version of the deficit round robin algorithm to schedule tenant requests, and has local weight adjustment and slow tenant handling to improve the system throughput. Empirical results show that our approach is able to provide fair share for multi-tenancy.
@inproceedings{
 title = {Multi-tenant fair share in NoSQL data stores},
 type = {inproceedings},
 year = {2014},
 id = {2cd5b545-5b80-3467-a7a8-4b2ffdabceef},
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 abstract = {© 2014 IEEE. NoSQL data stores see considerable attention today in big data, cloud hosted environments because of their fault tolerance, distribution and high availability. Shared NoSQL data stores are preferred for their ability to serve multiple tenants simultaneously which can improve resource utilization and lower management costs. Fair share in this setting can be a problem in that NoSQL data stores can be weak in preventing interference between tenants. We propose a methodology for multi-tenant fair share in a NoSQL store, in particular Cassandra. The approach uses an extended version of the deficit round robin algorithm to schedule tenant requests, and has local weight adjustment and slow tenant handling to improve the system throughput. Empirical results show that our approach is able to provide fair share for multi-tenancy.},
 bibtype = {inproceedings},
 author = {Zeng, J. and Plale, B.},
 doi = {10.1109/CLUSTER.2014.6968761},
 booktitle = {2014 IEEE International Conference on Cluster Computing, CLUSTER 2014}
}

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