• DocumentCode
    59988
  • Title

    Workload-Aware Credit Scheduler for Improving Network I/O Performance in Virtualization Environment

  • Author

    Haibing Guan ; Ruhui Ma ; Jian Li

  • Author_Institution
    Dept. of Comput., Shanghai Jiao Tong Univ., Shanghai, China
  • Volume
    2
  • Issue
    2
  • fYear
    2014
  • fDate
    April-June 1 2014
  • Firstpage
    130
  • Lastpage
    142
  • Abstract
    Single-root I/O virtualization (SR-IOV) has become the de facto standard of network virtualization in cloud infrastructure. Owing to the high interrupt frequency and heavy cost per interrupt in high-speed network virtualization, the performance of network virtualization is closely correlated to the computing resource allocation policy in Virtual Machine Manager (VMM). Therefore, more sophisticated methods are needed to process irregularity and the high frequency of network interrupts in high-speed network virtualization environment. However, the I/O-intensive and CPU-intensive applications in virtual machines are treated in the same manner since application attributes are transparent to the scheduler in hypervisor, and this unawareness of workload makes virtual systems unable to take full advantage of high performance networks. In this paper, we discuss the SR-IOV networking solution and show by experiment that the current credit scheduler in Xen does not utilize high performance networks efficiently. Hence we propose a novel workload-aware scheduling model with two optimizations to eliminate the bottleneck caused by scheduler. In this model, guest domains are divided into I/O-intensive domains and CPU-intensive domains according to their monitored behaviour. I/O-intensive domains can obtain extra credits that CPU-intensive domains are willing to share. In addition, the total number of credits available is adjusted to accelerate the I/O responsiveness. Our experimental evaluations show that the new scheduling models improve bandwidth and reduce response time, by keeping the fairness between I/O-intensive and CPU-intensive domains. This enables virtualization infrastructure to provide cloud computing services more efficiently and predictably.
  • Keywords
    cloud computing; processor scheduling; resource allocation; virtual machines; virtualisation; CPU-intensive applications; I-O responsiveness; I-O-intensive applications; SR-IOV networking solution; VMM; Xen; cloud computing services; cloud infrastructure; computing resource allocation policy; high-speed network virtualization environment; hypervisor; interrupt frequency; network I-O performance; single-root I-O virtualization; virtual machine manager; virtualization environment; workload-aware credit scheduler; workload-aware scheduling model; Cloud computing; Hardware; Monitoring; Resource management; Throughput; Virtual machining; Virtualization; Cloud computing; I/O virtualization; SR-IOV; Xen; hypervisor; scheduling;
  • fLanguage
    English
  • Journal_Title
    Cloud Computing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2168-7161
  • Type

    jour

  • DOI
    10.1109/TCC.2014.2314649
  • Filename
    6782279