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Shared Resource-Aware VM Scheduling in the Cloud


Commodity servers deployed in the data centers are now typically using the Non-Uniform Memory Access (NUMA) architecture. The NUMA multicore servers provide scalable system performance and cost-effective property. However, virtual machines (VMs) running on NUMA systems will access remote memory and contend for shared on-chip resources, which will decrease the overall performance of VMs and reduce the efficiency, fairness, and QoS that a virtualized system is capable to provide. In this project, we design and implement a shared resource-aware VM scheduler on NUMA multicore servers that are now commonly used in the cloud.

Shared Resource Usage Analysis

VM Performance Modeling and Prediction

Architecture Overview

Online VM Performance Monitoring

Shared Resource-Aware VM Scheduler on KVM Platform

Shared Resource-Aware VM Scheduler on Xen Platform

Future Work

  • Improving VM Performance and Server Utilization to Reduce Cost in the Cloud

  • Improving VM QoS guarantee in the multi-tenant cloud environment

  • An intelligent VM management system that provides both efficiency and fairness for the cloud users



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