An amateur's introduction to recursive query processing strategies
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
A flexible model for resource management in virtual private networks
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
A solver for the network testbed mapping problem
ACM SIGCOMM Computer Communication Review
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Rethinking virtual network embedding: substrate support for path splitting and migration
ACM SIGCOMM Computer Communication Review
A scalable, commodity data center network architecture
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
Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling
Proceedings of the 5th European conference on Computer systems
Online aggregation and continuous query support in MapReduce
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
SPAIN: COTS data-center Ethernet for multipathing over arbitrary topologies
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
HaLoop: efficient iterative data processing on large clusters
Proceedings of the VLDB Endowment
SecondNet: a data center network virtualization architecture with bandwidth guarantees
Proceedings of the 6th International COnference
Reining in the outliers in map-reduce clusters using Mantri
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
CIEL: a universal execution engine for distributed data-flow computing
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Mesos: a platform for fine-grained resource sharing in the data center
Proceedings of the 8th USENIX conference on Networked systems design and implementation
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
Improving datacenter performance and robustness with multipath TCP
Proceedings of the ACM SIGCOMM 2011 conference
No one (cluster) size fits all: automatic cluster sizing for data-intensive analytics
Proceedings of the 2nd ACM Symposium on Cloud Computing
FairCloud: sharing the network in cloud computing
Proceedings of the 10th ACM Workshop on Hot Topics in Networks
The price is right: towards location-independent costs in datacenters
Proceedings of the 10th ACM Workshop on Hot Topics in Networks
Re-optimizing data-parallel computing
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Hi-index | 0.00 |
In multi-tenant datacenters, jobs of different tenants compete for the shared datacenter network and can suffer poor performance and high cost from varying, unpredictable network performance. Recently, several virtual network abstractions have been proposed to provide explicit APIs for tenant jobs to specify and reserve virtual clusters (VC) with both explicit VMs and required network bandwidth between the VMs. However, all of the existing proposals reserve a fixed bandwidth throughout the entire execution of a job. In the paper, we first profile the traffic patterns of several popular cloud applications, and find that they generate substantial traffic during only 30%-60% of the entire execution, suggesting existing simple VC models waste precious networking resources. We then propose a fine-grained virtual network abstraction, Time-Interleaved Virtual Clusters (TIVC), that models the time-varying nature of the networking requirement of cloud applications. To demonstrate the effectiveness of TIVC, we develop Proteus, a system that implements the new abstraction. Using large-scale simulations of cloud application workloads and prototype implementation running actual cloud applications, we show the new abstraction significantly increases the utilization of the entire datacenter and reduces the cost to the tenants, compared to previous fixed-bandwidth abstractions.