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
Link To Document :
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