Proceedings of the seventeenth ACM symposium on Operating systems principles
Experiences with predicting resource performance on-line in computational grid settings
ACM SIGMETRICS Performance Evaluation Review
A Corpus for the Evaluation of Lossless Compression Algorithms
DCC '97 Proceedings of the Conference on Data Compression
Adaptive Online Data Compression
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Network Conscious Text Compression System (NCTCSys)
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Efficient End to End Data Exchange Using Configurable Compression
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Diagnosing performance overheads in the xen virtual machine environment
Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments
Adaptive On-the-Fly Compression
IEEE Transactions on Parallel and Distributed Systems
Measuring CPU overhead for I/O processing in the Xen virtual machine monitor
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
FoxyTechnique: tricking operating system policies with a virtual machine monitor
Proceedings of the 3rd international conference on Virtual execution environments
Virtual I/O scheduler: a scheduler of schedulers for performance virtualization
Proceedings of the 3rd international conference on Virtual execution environments
Bridging the gap between software and hardware techniques for I/O virtualization
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Profiling and modeling resource usage of virtualized applications
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
The Eucalyptus Open-Source Cloud-Computing System
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Nephele: efficient parallel data processing in the cloud
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Modeling virtual machine performance: challenges and approaches
ACM SIGMETRICS Performance Evaluation Review
Differential virtual time (DVT): rethinking I/O service differentiation for virtual machines
Proceedings of the 1st ACM symposium on Cloud computing
The impact of virtualization on network performance of amazon EC2 data center
INFOCOM'10 Proceedings of the 29th conference on Information communications
Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud
IEEE Transactions on Parallel and Distributed Systems
Evaluating Adaptive Compression to Mitigate the Effects of Shared I/O in Clouds
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
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Infrastructure as a Service clouds often use virtual machines to host different customers on the same physical hardware. This form of resource sharing can lead to unpredicatable performance degradations for the individual customer, especially with regard to data-intensive applications, which heavily depend on stable I/O characteristics. One traditional approach to cope with I/O fluctuations is adaptive online compression. In this paper we present a new scheme for adaptive online compression which has been explicitly designed to work in co-located virtual machine environments. In contrast to existing adaptive online compression schemes, the decision model of our approach does not rely on the system metrics CPU utilization and I/O bandwidth, which we demonstrate to be often displayed inaccurately inside XEN, KVM, and Amazon EC2-based virtual machines. Instead, it only considers the application data rate. Without requiring any calibration or training phase our adaptive compression scheme can improve the I/O throughput of virtual machines up to a factor of four as shown through extended experimental evaluations.