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2015 IEEE 8th International Conference on Cloud Computing (CLOUD) (2015)
New York City, NY, USA
June 27, 2015 to July 2, 2015
ISSN: 2159-6190
ISBN: 978-1-4673-7286-2
pp: 860-868
ABSTRACT
Geographically dispersed cloud data centers (DCs) enable web application providers to improve their services' response time and availability by deploying application replicas in multiple DCs. To allow applications requiring strong consistency to be deployed in multiple clouds, industry and academia have developed various scalable database systems that can guarantee strong inter-DC consistency with alleviated network overhead. For applications using these database systems, it is essential to take both the network latencies to the end users and the communication overhead of the databases into account when selecting the hosting DCs. In this paper, we study how to identify the satisfactory deployment plan (hosting DCs and request routing) considering SLO satisfaction, migration cost, and operational cost for applications using these databases. The proposed approach involves two steps. First, it searches the deployment plan with minimum amount of SLO violations using genetic algorithm when the application is first migrated to the clouds. Then it continuously optimizes the deployment in a certain time interval according to the changing workload and the current deployment plan. We illustrate how our approach works for the applications using two databases (Cassandra and Galera Cluster), and demonstrate the effectiveness of our approach through simulation studies using settings of two example applications (TPC-W and Twissandra). Our solution is extensible to applications using other database systems that have similar properties.
INDEX TERMS
Databases, Protocols, Genetic algorithms, Delays, Routing, Biological cells, Google
CITATION

C. Qu, R. N. Calheiros and R. Buyya, "SLO-Aware Deployment of Web Applications Requiring Strong Consistency Using Multiple Clouds," 2015 IEEE 8th International Conference on Cloud Computing (CLOUD), New York City, NY, USA, 2015, pp. 860-868.
doi:10.1109/CLOUD.2015.118
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