Title
POUX: Performance Optimization Strategy for Cloud Platforms Based on User Experience
Abstract
Cloud computing has been widely used in almost every areas of our life. System virtualization is one of the key technologies in cloud computing. However, it is a great challenge to achieve a balance among the virtual machines (VMs) in different physical machines (PMs) by migrating overloaded VMs to underloaded PMs while minimizing the number of VM migrations. Most of existing performance optimization strategies only concern about the hardware parameters (i.e., CPU, memory and I/O, etc.) of VMs, but the important user experience parameters (i.e., response time and through rate, etc.) have been ignored. We propose a novel Performance Optimization strategy based on User eXperience (POUX) for the cloud platform. To obtain the parameters of user experience, we design a management architecture of the cloud platform, and define the standardized interfaces between VMs and management center. Due to the unique characteristics of load balancing in the cloud platform, performance optimization problems are often NP-hard. Therefore, we propose a heuristic for automatic performance optimization, which plays a tradeoff among hardware utilization, user experience and the number of VM migrations. We use the CloudSim simulator and our deployed small-scale real-world testbed to evaluate the performance of POUX. Various experimental results have indicated that our cloud-based management architecture and performance optimization strategy not only significantly reduce the number of VM migrations, but also ensure a better user experience.
Year
DOI
Venue
2017
10.1109/BIGCOM.2017.60
2017 3rd International Conference on Big Data Computing and Communications (BIGCOM)
Keywords
Field
DocType
Virtualization,Virtual machine migration,Performance optimization,User experience
Virtualization,Data mining,User experience design,Heuristic,Virtual machine,Load balancing (computing),Computer science,Testbed,Optimization problem,Embedded system,Cloud computing,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-5386-3350-2
0
0.34
References 
Authors
15
5
Name
Order
Citations
PageRank
Zhijin Qiu182.79
Zhongwen Guo243.85
Yanan Sun300.34
Yingjian Liu432.82
Yu Wang5143287.32