Cost Effective Network Flow Measurement for Software Defined Networks: A Distributed Controller Scenario

Software-defined networking (SDN) has emerged as an evolutionary paradigm in datacenter networks by separating data from control plane and centralizing network decision making. Traffic flow measurement in SDN is relatively lightweight in comparison to the traditional methods. It enables flow measurement system to overcome the issues of traditional measurement systems, such as cost and accuracy by employing a centralized controller. Nevertheless, a full physically centralized controller introduces negative impacts on the network as well as the measurement system (i.e., introducing extra overhead or accuracy issues). However, few efforts have been devoted to measurement techniques in SDN distributed controller architecture, where every controller pulls its corresponding flow statistics, and these statistics are required to expose by only one single expression as if they are collected by one controller. Moreover, the imposed costs of flow measurement in distributed controller architecture are still an issue that remains unsolved. In this paper, we attempt to fill in this gap and present a novel and a practical solution for a cost-effective measurement system in SDN distributed controller deployment. We also propose a synchronization mechanism for aggregating traffic statistics in the multiple controller model. We evaluate our method through extensive emulations in a datacenter topology and present our findings to demonstrate the impact of multiple controllers on overhead and accuracy.

[1]  Arjan Durresi,et al.  A survey: Control plane scalability issues and approaches in Software-Defined Networking (SDN) , 2017, Comput. Networks.

[2]  Sakir Sezer,et al.  Queen ' s University Belfast-Research Portal Are We Ready for SDN ? Implementation Challenges for Software-Defined Networks , 2016 .

[3]  Xiao Zhang,et al.  CPI2: CPU performance isolation for shared compute clusters , 2013, EuroSys '13.

[4]  Pin Lv,et al.  Control plane of software defined networks: A survey , 2015, Comput. Commun..

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

[6]  Alistair Moffat,et al.  Lazy and Eager Approaches for the Set Cover Problem , 2014, ACSC.

[7]  Chen-Nee Chuah,et al.  LEISURE: Load-Balanced Network-Wide Traffic Measurement and Monitor Placement , 2015, IEEE Transactions on Parallel and Distributed Systems.

[8]  Sebastian Zander,et al.  A survey of covert channels and countermeasures in computer network protocols , 2007, IEEE Communications Surveys & Tutorials.

[9]  Christophe Diot,et al.  Reformulating the Monitor Placement Problem: Optimal Network-Wide Sampling , 2006 .

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

[11]  Benoit Claise,et al.  Cisco Systems NetFlow Services Export Version 9 , 2004, RFC.

[12]  Zhiyang Su,et al.  CeMon: A Cost-effective Flow Monitoring System in Software Defined Networks , 2015, Comput. Networks.

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

[14]  Sujata Banerjee,et al.  DevoFlow: cost-effective flow management for high performance enterprise networks , 2010, Hotnets-IX.

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

[16]  Jan Medved,et al.  OpenDaylight: Towards a Model-Driven SDN Controller architecture , 2014, Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014.

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

[18]  Minlan Yu,et al.  Software Defined Traffic Measurement with OpenSketch , 2013, NSDI.

[19]  Raouf Boutaba,et al.  Design considerations for managing wide area software defined networks , 2014, IEEE Communications Magazine.

[20]  Andrew C. Myers,et al.  JFlow: practical mostly-static information flow control , 1999, POPL '99.

[21]  Juliane Junker,et al.  Computer Organization And Design The Hardware Software Interface , 2016 .

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

[23]  Antonio Pescapè,et al.  Challenges and solution for measuring available bandwidth in software defined networks , 2017, Comput. Commun..

[24]  K. Kalpana,et al.  Active and Passive Network Measurements : A Survey , 2011 .

[25]  Didier Colle,et al.  Fast failure recovery for in-band OpenFlow networks , 2013, 2013 9th International Conference on the Design of Reliable Communication Networks (DRCN).

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

[27]  Kui Yi,et al.  32-bit RISC CPU Based on MIPS Instruction Fetch Module Design , 2009, 2009 International Joint Conference on Artificial Intelligence.

[28]  Xiang-Yang Li,et al.  Minimizing Flow Statistics Collection Cost Using Wildcard-Based Requests in SDNs , 2017, IEEE/ACM Transactions on Networking.

[29]  Kim-Kwang Raymond Choo,et al.  A multi-objective software defined network traffic measurement , 2017 .

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

[31]  Fang Hao,et al.  Towards an elastic distributed SDN controller , 2013, HotSDN '13.