›› 2018, Vol. 33 ›› Issue (2): 277-285.doi: 10.1007/s11390-018-1819-2

Special Issue: Computer Networks and Distributed Computing

• Special Section on Computer Networks and Distributed Computing • Previous Articles     Next Articles

LLMP: Exploiting LLDP for Latency Measurement in Software-Defined Data Center Networks

Yang Li1, Student Member, CCF, Zhi-Ping Cai1*, Senior Member, CCF, Member, IEEE, Hong Xu2, Member, ACM, IEEE   

  1. 1 College of Computer, National University of Defense Technology, Changsha 410073, China;
    2 Department of Computer Science, City University of Hong Kong, Hong Kong 999077, China
  • Received:2017-07-31 Revised:2017-07-31 Online:2018-03-05 Published:2018-03-05
  • Contact: Zhi-Ping Cai E-mail:zpcai@nudt.edu.cn
  • About author:Yang Li received his B.S. degree in computer science from Ocean University of China, Qingdao, in 2014. Then he received his M.S. degree in computer science and technology from National University of Defense Technology, Changsha, in 2017. His research interests are mainly in software-defined network (SDN) and network measurement
  • Supported by:

    This work was supported by the National Natural Science Foundation of China under Grant Nos. 61379145, 61501482, 61762033.

The administrators of data center networks have to continually monitor path latency to detect network anomaly quickly and ensure the efficient operation of the networks. In this work, we propose Link Layer Measurement Protocol (LLMP), a prototype latency measuring framework based on the Link Layer Discovery Protocol (LLDP). LLDP is utilized by the controller to discover network topology dynamically. We insert timestamps into the optional LLDPTLV field in LLDP, so that the controller can estimate latency on any single link. The framework utilizes a reactive measurement approach without injecting any probe packets to the network. Our experiments show that the latency of a link can be measured accurately by LLMP. In relatively complex network conditions, LLMP can still maintain a high accuracy. We store the LLMP measurement results into a latency matrix, which can be used to infer the path latency.

[1] Das A, Lumezanu C, Zhang Y et al. Transparent and flexible network management for big data processing in the cloud. In Proc. the 5th USENIX Workshop on Hot Topics in Cloud Computing, June 2013.

[2] Duffield N G, Grossglauser M. Trajectory sampling for direct traffic observation. IEEE/ACM Transactions on Networking, 2001, 9(3):280-292.

[3] Yu C, Lumezanu C, Zhang Y et al. FlowSense:Monitoring network utilization with zero measurement cost. In Proc. PAM, Oct. 2013, pp.31-34.

[4] Rotsos C, Sarrar N, Uhlig S et al. OFLOPS:An open framework for OpenFlow switch evaluation. In Proc. PAM, Mar. 2012, pp.85-95.

[5] Huang D Y, Yocum K, Snoeren A C. High-fidelity switch models for software-defined network emulation. In Proc. HotSDN, Aug. 2013, pp.43-48.

[6] Kreutz D, Ramos F M V, Paulo Esteves Verssimo et al. Software-defined networking:A comprehensive survey. Proceedings of the IEEE, 2015, 103(1):14-76.

[7] van Adrichem N L M, Doerr C, Kuipers F A. OpenNetMon:Network monitoring in OpenFlow software-defined networks. In Proc. Network Operations and Management Symposium (NOMS), May 2014.

[8] Yu C, Lumezanu C, Sharma A et al. Software-defined latency monitoring in data center networks. In Proc. PAM, Mar. 2015, pp.360-372.

[9] Cui Y, Xiao S, Liao C et al. Data centers as softwaredefined networks:Traffic redundancy elimination with wireless cards at routers. IEEE Journal on Selected Areas in Communications, 2013, 31(12):2658-2672.

[10] Han K, Hu Z, Luo J et al. RUSH:Routing and scheduling for hybrid data center networks. In Proc. IEEE INFOCOM, Apr. 2015, pp.415-423.

[11] Narisetty R R, Dane L, Malishevskiy A et al. OpenFlow configuration protocol:Implementation for the of management plane. In Proc. the 2nd GENI Research and Educational Experiment Workshop, Mar. 2013, pp.66-67.

[12] Mckeown N, Anderson T, Balakrishnan H et al. OpenFlow:Enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 2008, 38(2):69-74.

[13] Dhawan M, Poddar R, Mahajan K et al. SPHINX:Detecting security attacks in software-defined networks. In Proc. NDSS, Feb 2015.

[14] Yu M, Jose L, Miao R. Software-defined traffic measurement with OpenSketch. In Proc. NSDI, Apr. 2013, pp.29-42.

[15] Braun W, Menth M. Software-defined networking using OpenFlow:Protocols, applications and architectural design choices. Future Internet, 2014, 6(2):302-336.

[16] Kim H, Feamster N. Improving network management with software-defined networking. IEEE Communications Magazine, 2013, 51(2):114-119.

[17] Chowdhury S R, Bari M F, Ahmed R et al. PayLess:A low cost network monitoring framework for software-defined networks. In Proc. NOMS 2014, May 2014, pp.1-9.

[18] Gill P, Jain N, Nagappan N. Understanding network failures in data centers:Measurement, analysis, and implications. ACM SIGCOMM Computer Communication Review, 2011, 41(4):350-361.

[19] Gandhi R, Liu H H, Hu Y C et al. Duet:Cloud scale load balancing with hardware and software. ACM SIGCOMM Computer Communication Review, 2015, 44(4):27-38.

[20] Xie D, Ding N, Hu Y C et al. The only constant is change:Incorporating time-varying network reservations in data centers. ACM SIGCOMM Computer Communication Review, 2012, 42(4):199-210.

[21] Zhang H, Cai Z P, Liu Q et al. A survey on security-aware measurement in SDN. Security and Communication Networks, 2018, doi:10.1155/2018/2459154. (to be appeared)

[22] Xia J, Cai Z P, Hu G et al. An active defense solution for ARP spoofing in OpenFlow network. Chinese Journal of Electronics, 2018. (to be appeared)
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[1] Wu Yunzeng;. On the Development of Applications of Logic in Programming[J]. , 1987, 2(1): 30 -34 .
[2] Zhang Bo; Zhang Ling;. Statistical Heuristic Search[J]. , 1987, 2(1): 1 -11 .
[3] Meng Liming; Xu Xiaofei; Chang Huiyou; Chen Guangxi; Hu Mingzeng; Li Sheng;. A Tree-Structured Database Machine for Large Relational Database Systems[J]. , 1987, 2(4): 265 -275 .
[4] Lin Qi; Xia Peisu;. The Design and Implementation of a Very Fast Experimental Pipelining Computer[J]. , 1988, 3(1): 1 -6 .
[5] Sun Chengzheng; Tzu Yungui;. A New Method for Describing the AND-OR-Parallel Execution of Logic Programs[J]. , 1988, 3(2): 102 -112 .
[6] Zhang Bo; Zhang Tian; Zhang Jianwei; Zhang Ling;. Motion Planning for Robots with Topological Dimension Reduction Method[J]. , 1990, 5(1): 1 -16 .
[7] Min Yinghua; Yashwant K. Malaiya; Jin Boping;. Aliasing Errors in Parallel Signature Analyzers[J]. , 1990, 5(1): 24 -40 .
[8] Wang Dingxing; Zheng Weimin; Du Xiaoli; Guo Yike;. On the Execution Mechanisms of Parallel Graph Reduction[J]. , 1990, 5(4): 333 -346 .
[9] Klaus Buchenrieder;. Standard-Cell Placement from Functional Descriptions[J]. , 1991, 6(1): 37 -46 .
[10] Zhou Quan; Wei Daozheng;. A Complete Critical Path Algorithm for Test Generation of Combinational Circuits[J]. , 1991, 6(1): 74 -82 .

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