Optimization of CPU Scheduling in Virtual Machine Environments

Data centres and other infrastructures in the field of information technology suffer from the major issue of ‘server sprawl’, a term used to depict the situation wherein a number of servers consume resources inefficiently, when compared to the business value of outcome obtained from them. Consolidation of servers, rather than dedicating whole servers to individual applications, optimizes the usage of hardware resources, and virtualization achieves this by allowing multiple servers to share a single hardware platform. Server virtualization is facilitated by the usage of hypervisors, among which Xen is widely preferred because of its dual virtualization modes, virtual machine migration support and scalability. This research work involves an analysis of the CPU scheduling algorithms incorporated into Xen, on the basis of the algorithm’s performance in different workload scenarios. In addition to performance evaluation, the results obtained lay emphasis on the importance of compute intensive or I/O intensive domain handling capacity of a hypervisor’s CPU scheduling algorithm in virtualized server environments. Based on this knowledge, the selection of CPU scheduler in a hypervisor can be aligned with the requirements of the hosted applications. A new credit-based VCPU scheduling scheme is proposed, in which the credits remaining for each VCPU after every accounting period plays a significant role in the scheduling decision. The proposed scheduling strategy allows those VCPUs of I/O intensive domains to supersede others, in order to favour the reduction of I/O bound domain response times and the subsequent bottleneck in the CPU run queue. Though a small percentage of context switch overhead is introduced, the results indicate substantial improvement of I/O handling and fairness in re-source allocation between the host and guest domains