PMAX: tenant placement in multitenant databases for profit maximization

There has been a great interest in exploiting the cloud as a platform for database as a service. As with other cloud-based services, database services may enjoy cost efficiency through consolidation: hosting multiple databases within a single physical server. Aggressive consolidation, however, may hurt the service quality, leading to SLA violation penalty, which in turn reduces the total business profit, called SLA profit. In this paper, we consider the problem of tenant placement in the cloud for SLA profit maximization, which, as will be shown in the paper, is strongly NP-hard. We propose SLA profit-aware solutions for database tenant placement based on our model for expected penalty computation for multitenant servers. Specifically, we present two approximation algorithms, which have constant approximation ratios, and we further discuss improving the quality of tenant placement using a dynamic programming algorithm. Extensive experiments based on TPC-W workload verified the performance of the proposed approaches.

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