Adaptively parallelizing distributed range queries
Proceedings of the VLDB Endowment
ESQP: an efficient SQL query processing for cloud data management
CloudDB '10 Proceedings of the second international workshop on Cloud data management
Adaptive query execution for data management in the cloud
CloudDB '10 Proceedings of the second international workshop on Cloud data management
Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
Workload-aware database monitoring and consolidation
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A Cost-Aware Elasticity Provisioning System for the Cloud
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Deadline Queries: Leveraging the Cloud to Produce On-Time Results
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
How a consumer can measure elasticity for cloud platforms
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Adaptive Provisioning of Stream Processing Systems in the Cloud
ICDEW '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering Workshops
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Cloud computing is a very promising paradigm of service-oriented computing. One major benefit of cloud computing its elasticity, i.e., the system's capacity to provide and remove resources automatically at runtime. For that, it is essential to design and implement an efficient and effective technique that takes full advantage of the system's potential flexibility. This paper presents a non-intrusive approach that monitors the performance of relational DBMSs in a cloud infrastructure, and automatically makes decisions to maximize the efficiency of the provider's environment while still satisfying agreed upon "service level agreements"(SLAs). Our experiments conducted on Amazon's cloud infrastructure, confirm that our technique is capable of dynamically adjusting the system's allocated resources observing the SLA.