Cross-layer optimization for virtual machine resource management

Ming Zhao, Lixi Wang, Yun Lv, Jing Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Virtualized systems (e.g., public and private clouds) are playing an increasingly vital role to support the computing of applications from different domains. Existing resource management solutions in such systems typically treat virtual machines (VMs) as black boxes, which presents a hurdle to achieving application-desired Quality of Service (QoS). This paper advocates the cooperation between VM host- and guest-layer schedulers for optimizing the resource management and application performance. It presents an approach to such cross-layer optimization by enabling the host-layer scheduler to feedback resource allocation decisions and adapt guest-layer application configurations. As case studies, the proposed approach is applied to virtualized databases and map services which have challenging dynamic and complex resource demands as well as sophisticated configurations. Specifically, for databases, the proposed approach adapts query executions by tuning the cost model parameters according to the available storage bandwidth and memory capacity. For map services, it adapts the quality of returned map imagery in order to meet the response time target as the workload intensity and available network bandwidth change over time. A prototype of the proposed approach is implemented on Xen and Hyper-V VMs, and evaluated using a TPC-H based database workload and a TerraFly-based map service workload. The results show that with the proposed host-to-guest application adaptation, the TPC-H workload improves its performance by 33.5%, and the TerraFly workload improves the map imagery quality by 40% and always meets its response time target, compared to the schemes without adaptation.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Cloud Engineering, IC2E 2018
EditorsJie Li, Abhishek Chandra, Tian Guo, Ying Cai
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781538650080
StatePublished - May 16 2018
Event2018 IEEE International Conference on Cloud Engineering, IC2E 2018 - Orlando, United States
Duration: Apr 17 2018Apr 20 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Cloud Engineering, IC2E 2018


Other2018 IEEE International Conference on Cloud Engineering, IC2E 2018
Country/TerritoryUnited States


  • Cross-layer optimization
  • Resource management
  • Virtual machine

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture


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