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Variations in Performance and Scalability: An Experimental Study in IaaS Clouds using Multi-Tier Workloads
PrePrint
ISSN: 1939-1374
Deepal Jayasinghe, Georgia Institute of Technology, Atlanta
Simon Malkowski, Georgia Institute of Technology, Atlanta
Jack Li, Georgia Institute of Technology, Atlanta
Qingyang Wang, Georgia Institute of Technology, Atlanta
Zhikui Wang, HP Labs, Palo Alto
Calton Pu, Georgia Institute of Technology, Atlanta
Through extensive experimental measurements, we show variance in performance and scalability of clouds for two non-trivial scenarios. In the first scenario, we target the public Infrastructure as a Service clouds, and study the case when a multi-tier application is migrated from a traditional datacenter to one of the three IaaS clouds. To validate our findings in the first scenario, we conduct similar study with three private clouds built using three mainstream hypervisors. We used the RUBBoS benchmark and compared its performance and scalability when hosted in Amazon EC2, Open Cirrus, and Emulab. Our results show that a best-performing configuration in one cloud can become the worst-performing configuration in another cloud. Subsequently, we identified several system level bottlenecks such as high context switching and network driver processing overheads that degraded the performance. We experimentally evaluate concrete alternative approaches as practical solutions to address these problems. We then built the three private clouds using a commercial hypervisor (CVM), Xen, and KVM respectively and evaluated performance characteristics using both RUBBoS and Cloudstone applications. The three clouds show significant performance variations; for instance, Xen outperforms CVM by 75% on the read-write RUBBoS workload and CVM outperforms Xen by over 10% on the Cloudstone workload.
Index Terms:
Distributed databases,Client/server and multitier systems,Distributed Systems,Distributed applications,Measurement,evaluation,modeling,simulation of multiple-processor systems,Test execution,Testing tools,Measurements
Citation:
Deepal Jayasinghe, Simon Malkowski, Jack Li, Qingyang Wang, Zhikui Wang, Calton Pu, "Variations in Performance and Scalability: An Experimental Study in IaaS Clouds using Multi-Tier Workloads," IEEE Transactions on Services Computing, 01 Oct. 2013. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TSC.2013.46>
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