TY - GEN
T1 - Let me rephrase that
T2 - 2017 Symposium on SDN Research, SOSR 2017
AU - Prabhu, Santhosh
AU - Dong, Mo
AU - Meng, Tong
AU - Godfrey, P. Brighten
AU - Caesar, Matthew
N1 - Funding Information:
This work was supported by NSF CNS Award #1513906 and by the Maryland Procurement Office under Contract No. H98230-14-C-0141.
Publisher Copyright:
© 2017 ACM.
PY - 2017/4/3
Y1 - 2017/4/3
N2 - Enterprise networks today have highly diverse correctness requirements and relatively common performance objectives. As a result, preferred abstractions for enterprise networks are those which allow matching correctness specification, while transparently managing performance. Existing SDN network management architectures, however, bundle correctness and performance as a single abstraction. We argue that this creates an SDN ecosystem that is unnecessarily hard to build, maintain and evolve. We advocate a separation of the diverse correctness abstractions from generic performance optimization, to enable easier evolution of SDN controllers and platforms. We propose Oreo, a first step towards a common and relatively transparent performance optimization layer for SDN. Oreo performs the optimization by first building a model that describes every flow in the network, and then performing network-wide, multi-objective optimization based on this model without disrupting higher level correctness.
AB - Enterprise networks today have highly diverse correctness requirements and relatively common performance objectives. As a result, preferred abstractions for enterprise networks are those which allow matching correctness specification, while transparently managing performance. Existing SDN network management architectures, however, bundle correctness and performance as a single abstraction. We argue that this creates an SDN ecosystem that is unnecessarily hard to build, maintain and evolve. We advocate a separation of the diverse correctness abstractions from generic performance optimization, to enable easier evolution of SDN controllers and platforms. We propose Oreo, a first step towards a common and relatively transparent performance optimization layer for SDN. Oreo performs the optimization by first building a model that describes every flow in the network, and then performing network-wide, multi-objective optimization based on this model without disrupting higher level correctness.
KW - Optimization
KW - Software-defined networking
UR - http://www.scopus.com/inward/record.url?scp=85018972490&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018972490&partnerID=8YFLogxK
U2 - 10.1145/3050220.3050226
DO - 10.1145/3050220.3050226
M3 - Conference contribution
AN - SCOPUS:85018972490
T3 - SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research
SP - 41
EP - 47
BT - SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research
PB - Association for Computing Machinery
Y2 - 3 April 2017 through 4 April 2017
ER -