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Adaptive Resource Provisioning for Virtualized Servers Using Kalman Filters

Kalyvianaki, E., Charalambous, T. & Hand, S. (2014). Adaptive Resource Provisioning for Virtualized Servers Using Kalman Filters. ACM Transactions on Autonomous and Adaptive Systems, 9(2), 10. doi: 10.1145/2626290


Resource management of virtualized servers in data-centres has become a critical task, since it enables costeffective consolidation of server applications. Resource management is an important and challenging task, especially for multi-tier applications with unpredictable time-varying workloads. Work in resource management using control theory has shown clear benefits of dynamically adjusting resource allocations to match fluctuating workloads. However, little work has been done towards adaptive controllers for unknown workload types. This work presents a new resource management scheme that incorporates the Kalman filter into feedback controllers to dynamically allocate CPU resources to virtual machines hosting server applications. We present a set of controllers that continuously detect and self-adapt to unforeseen workload changes. Furthermore, our most advanced controller also self-configures itself without any a priori information and with a small 4.8% performance penalty in the case of high intensity workload changes. In addition, our controllers are enhanced to deal with multi-tier server applications: by using the pair-wise resource coupling between tiers, they improve server response to large workload increases as compared to controllers with no such resource-coupling mechanism. Our approaches are evaluated and their performance is illustrated on a 3-tier Rubis benchmark web-site deployed on a prototype Xen-virtualized cluster.

Publication Type: Article
Additional Information: © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS, 2014, 9(2),
Publisher Keywords: Kalman filter, feedback control, multi-tier server applications, resource management, virtual machines
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
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