ACM Transactions on Computer Systems (TOCS)
SEDA: an architecture for well-conditioned, scalable internet services
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Stardust: tracking activity in a distributed storage system
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Argon: performance insulation for shared storage servers
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
Ethane: taking control of the enterprise
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Cloud control with distributed rate limiting
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
OpenFlow: enabling innovation in campus networks
ACM SIGCOMM Computer Communication Review
PARDA: proportional allocation of resources for distributed storage access
FAST '09 Proccedings of the 7th conference on File and storage technologies
Onix: a distributed control platform for large-scale production networks
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
mClock: handling throughput variability for hypervisor IO scheduling
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Sierra: practical power-proportionality for data center storage
Proceedings of the sixth conference on Computer systems
Diagnosing performance changes by comparing request flows
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Tesseract: a 4D network control plane
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Towards predictable datacenter networks
Proceedings of the ACM SIGCOMM 2011 conference
Fast crash recovery in RAMCloud
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
Differentiated storage services
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
Less is more: trading a little bandwidth for ultra-low latency in the data center
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Multi-resource fair queueing for packet processing
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
FairCloud: sharing the network in cloud computing
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Performance isolation and fairness for multi-tenant cloud storage
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Cake: enabling high-level SLOs on shared storage systems
Proceedings of the Third ACM Symposium on Cloud Computing
Composing software-defined networks
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Chatty tenants and the cloud network sharing problem
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Participatory networking: an API for application control of SDNs
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
SIMPLE-fying middlebox policy enforcement using SDN
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
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In data centers, the IO path to storage is long and complex. It comprises many layers or "stages" with opaque interfaces between them. This makes it hard to enforce end-to-end policies that dictate a storage IO flow's performance (e.g., guarantee a tenant's IO bandwidth) and routing (e.g., route an untrusted VM's traffic through a sanitization middlebox). These policies require IO differentiation along the flow path and global visibility at the control plane. We design IOFlow, an architecture that uses a logically centralized control plane to enable high-level flow policies. IOFlow adds a queuing abstraction at data-plane stages and exposes this to the controller. The controller can then translate policies into queuing rules at individual stages. It can also choose among multiple stages for policy enforcement. We have built the queue and control functionality at two key OS stages-- the storage drivers in the hypervisor and the storage server. IOFlow does not require application or VM changes, a key strength for deployability. We have deployed a prototype across a small testbed with a 40 Gbps network and storage devices. We have built control applications that enable a broad class of multi-point flow policies that are hard to achieve today.