Scale the Data Plane of Software-Defined Networks: a Lazy Rule Placement Approach
Qing Li, Nanyang Huang, Yong Jiang, Richard Sinnott, Mingwei Xu
2020 IEEE 40TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS) | IEEE COMPUTER SOC | Published : 2020
—Data plane programming languages enable administrators of Software-Defined Networks (SDNs) to perform fine-grained flow control by compiling high-level policies into low-level rules and deploying rules in the data plane. However, it is difficult to scale the data plane with the dynamics of network traffic and the limited storage space of switches. In this paper, we propose a lazy OpenFlow Rule Placement (ORP) framework to enforce control polices and scale the SDN data plane by placing and reusing wildcard rules. We provide an offline rule placement scheme to meet performance objectives under real-world constraints. To handle dynamic traffic and perform incremental rule updates, we design an..View full abstract
Awarded by National Natural Science Foundation of China
Awarded by Guangdong Province Key Area RD Program
Awarded by project "PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications"
Awarded by Shenzhen Key Lab of Software Defined Networking
This work is supported by National Natural Science Foundation of China under grant No. 61972189, Guangdong Province Key Area R&D Program under grant No. 2018B010113001, the project "PCL Future Greater-Bay Area Network Facilities for Large-scale Experiments and Applications (PCL2018KP001)" and the Shenzhen Key Lab of Software Defined Networking under grant No. ZDSYS20140509172959989.