Autonomic benchmarking for cloud infrastructures: an economic optimization model
Proceedings of the 1st ACM/IEEE workshop on Autonomic computing in economics
TRACON: interference-aware scheduling for data-intensive applications in virtualized environments
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Packet aggregation based network I/O virtualization for cloud computing
Computer Communications
FIOS: a flexible virtualized I/O subsystem to alleviate interference among virtual machines
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Evaluation of the HPC challenge benchmarks in virtualized environments
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing - Volume 2
An experimental study of cascading performance interference in a virtualized environment
ACM SIGMETRICS Performance Evaluation Review
Bobtail: avoiding long tails in the cloud
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Survey Cloud monitoring: A survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Measurement Study of Data-Intensive Network Traffic Patterns in a Private Cloud
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
COSCAnet: Virtualized Sockets for Scalable and Flexible PaaS Applications
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
| Hi-index | 0.00 |
Virtualization is a key technology for cloud based data centers to implement the vision of infrastructure as a service (IaaS) and to promote effective server consolidation and application consolidation. However, current implementation of virtual machine monitor does not provide sufficient performance isolation to guarantee the effectiveness of resource sharing, especially when the applications running on multiple virtual machines of the same physical machine are competing for computing and communication sources. In this paper, we present our performance measurement study of network I/O applications in virtualized cloud. We focus our measurement based analysis on performance impact of co-locating applications in a virtualized cloud in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. Our results show that by strategically co-locating network I/O applications, performance improvement for cloud consumers can be as high as 34%, and the cloud providers can achieve over 40% performance gain.