Autonomic resource allocation in virtualized data centers

Virtualization has been widely adopted in data centers for improving efficiency and flexibility. Multiple applications are co-hosted in virtualized data centers. In order to meet the Service Level Agreements (SLA), how to allocate resources for multiple applications is an important and challenging task, especially when dealing with fluctuating workloads and complex server applications. Virtual Machine Monitor provides fine-grained resource allocation and live migration. In this paper, we develop RTCOIN-Qclouds, a response time-aware, cost-aware and interference-aware control framework that tunes resource allocation, which ensures a high level of meeting the SLAs. Every physical machine's resources are assigned to multiple virtual machines which run on it based on application's response time, rather than traditional methods based on resource utilization. Virtual machine migration allows data centers to rebalance workloads across physical machines. However, migration actions may lead to performance impact during the migration process. Current virtualization techniques do not provide effective performance isolation between virtual machines (VMs). Specially, hidden contention for physical resources impacts performance differently in different virtual machines. As to the problem of selecting which virtual machines to be migrated, we consider migration cost. As to the problem of selecting which physical machine to be placed, we consider performance interference. Furthermore, we experimentally validate the effectiveness of response time-aware resource allocation in our framework using microbenchmarks.