Dynamic control plane management for software‐defined networks

Summary Software-defined network (SDN) is an emerging network paradigm that allows flexible network management by providing programmability from a separated control plane. Because of the centralized management scheme that SDN adopts, intensive control plane overhead incurs as the scale of SDN increases. The control plane overhead is mainly caused by a massive amount of control messages generated during data plane monitoring and reactive flow instantiation. By far, very few works have addressed the overhead issue on reaction flow instantiation; therefore, we mainly focus on alleviating such overhead in this work. To achieve this goal, we propose a new control plane management (CPMan) method. CPMan aims to realize the following two objectives: first, reduce the number of control messages exchanged through the control channel and second, evenly distribute the control workload across multiple controllers to mitigate the potential performance bottleneck. To realize the former, we propose a lightweight feedback loop-based control scheme, whereas for the latter, we propose a dynamic switch-to-controller (DSC) placement scheme. To show the feasibility of our proposal, we implemented a prototype of the two proposed schemes on top of a carrier-grade SDN controller and validated its performance in an emulated network. We achieved approximately 57.13% overhead reduction with feedback loop-based control scheme, while achieved approximately 98.68% balance ratio with DSC placement scheme. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[2]  Rob Sherwood,et al.  The controller placement problem , 2012, HotSDN '12.

[3]  Monia Ghobadi,et al.  OpenTM: Traffic Matrix Estimator for OpenFlow Networks , 2010, PAM.

[4]  Morten Lauge Pedersen,et al.  Encyclopedia of Life Support Systems (EOLSS) , 2005 .

[5]  Harsha V. Madhyastha,et al.  FlowSense: Monitoring Network Utilization with Zero Measurement Cost , 2013, PAM.

[6]  Ramesh Govindan,et al.  An empirical study of router response to large BGP routing table load , 2002, IMW '02.

[7]  Fernando A. Kuipers,et al.  OpenNetMon: Network monitoring in OpenFlow Software-Defined Networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[8]  Rob Sherwood,et al.  The controller placement problem , 2012, HotSDN@SIGCOMM.

[9]  Xirong Que,et al.  On reliability-optimized controller placement for Software-Defined Networks , 2014, China Communications.

[10]  Michalis Faloutsos,et al.  ReSurf: Reconstructing web-surfing activity from network traffic , 2013, 2013 IFIP Networking Conference.

[11]  Alexander Shalimov,et al.  Advanced study of SDN/OpenFlow controllers , 2013 .

[12]  Yashar Ganjali,et al.  HyperFlow: A Distributed Control Plane for OpenFlow , 2010, INM/WREN.

[13]  Mohamed Faten Zhani,et al.  Dynamic Controller Provisioning in Software Defined Networks , 2013, Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013).

[14]  Jia Wang,et al.  Scalable flow-based networking with DIFANE , 2010, SIGCOMM '10.

[15]  Martín Casado,et al.  Extending Networking into the Virtualization Layer , 2009, HotNets.

[16]  Stanislav Lange,et al.  Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks , 2015, IEEE Transactions on Network and Service Management.

[17]  Sujata Banerjee,et al.  DevoFlow: scaling flow management for high-performance networks , 2011, SIGCOMM 2011.

[18]  Martín Casado,et al.  Onix: A Distributed Control Platform for Large-scale Production Networks , 2010, OSDI.

[19]  Yashar Ganjali,et al.  Kandoo: a framework for efficient and scalable offloading of control applications , 2012, HotSDN '12.

[20]  Matthew Roughan,et al.  The Internet Topology Zoo , 2011, IEEE Journal on Selected Areas in Communications.

[21]  Antonio Pescapè,et al.  A tool for the generation of realistic network workload for emerging networking scenarios , 2012, Comput. Networks.

[22]  Sujata Banerjee,et al.  DevoFlow: scaling flow management for high-performance networks , 2011, SIGCOMM.

[23]  Peng-Yeng Yin,et al.  Multi-objective task allocation in distributed computing systems by hybrid particle swarm optimization , 2007, Appl. Math. Comput..

[24]  Raouf Boutaba,et al.  PayLess: A low cost network monitoring framework for Software Defined Networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[25]  Minlan Yu,et al.  Scalable flow-based networking with DIFANE , 2010, SIGCOMM 2010.

[26]  Rob Sherwood,et al.  On Controller Performance in Software-Defined Networks , 2012, Hot-ICE.

[27]  Pavlin Radoslavov,et al.  ONOS: towards an open, distributed SDN OS , 2014, HotSDN.

[28]  Jae-Hyoung Yoo,et al.  CPMan: Adaptive control plane management for software-defined networks , 2015, 2015 IEEE Conference on Network Function Virtualization and Software Defined Network (NFV-SDN).

[29]  Nick McKeown,et al.  Reproducible network experiments using container-based emulation , 2012, CoNEXT '12.