End-to-end Internet packet dynamics
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
The macroscopic behavior of the TCP congestion avoidance algorithm
ACM SIGCOMM Computer Communication Review
A flexible model for resource management in virtual private networks
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Ten fallacies and pitfalls on end-to-end available bandwidth estimation
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
End-to-end estimation of the available bandwidth variation range
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
On the predictability of large transfer TCP throughput
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Discarte: a disjunctive internet cartographer
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
VL2: a scalable and flexible data center network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Understanding data center traffic characteristics
Proceedings of the 1st ACM workshop on Research on enterprise networking
The impact of virtualization on network performance of amazon EC2 data center
INFOCOM'10 Proceedings of the 29th conference on Information communications
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Hedera: dynamic flow scheduling for data center networks
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
CloudCmp: comparing public cloud providers
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Network traffic characteristics of data centers in the wild
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
Sharing the data center network
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Towards predictable datacenter networks
Proceedings of the ACM SIGCOMM 2011 conference
Purlieus: locality-aware resource allocation for MapReduce in a cloud
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Traffic models in broadband networks
IEEE Communications Magazine
Packet Trains--Measurements and a New Model for Computer Network Traffic
IEEE Journal on Selected Areas in Communications
Bandwidth estimation: metrics, measurement techniques, and tools
IEEE Network: The Magazine of Global Internetworking
Opening up black box networks with CloudTalk
HotCloud'12 Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing
On Optimizing MMVEs in Network-Aware Clouds
Proceedings of International Workshop on Massively Multiuser Virtual Environments
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Cloud computing infrastructures are increasingly being used by network-intensive applications that transfer significant amounts of data between the nodes on which they run. This paper shows that tenants can do a better job placing applications by understanding the underlying cloud network as well as the demands of the applications. To do so, tenants must be able to quickly and accurately measure the cloud network and profile their applications, and then use a network-aware placement method to place applications. This paper describes Choreo, a system that solves these problems. Our experiments measure Amazon's EC2 and Rackspace networks and use three weeks of network data from applications running on the HP Cloud network. We find that Choreo reduces application completion time by an average of 8%-14% (max improvement: 61%) when applications are placed all at once, and 22%-43% (max improvement: 79%) when they arrive in real-time, compared to alternative placement schemes.