Welcome to Journal of University of Chinese Academy of Sciences,Today is

Batch routing in SDN networks with resource preference consideration

  • FANG Qiusheng ,
  • HONG Peilin
Expand
  • Key Laboratory of Wireless-Optical Communications of Chinese Academy of Sciences, School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China

Received date: 2015-12-09

  Revised date: 2016-02-29

  Online published: 2016-07-15

Abstract

In SDN networks, the limited flow tables at switches confine the number of flows which can pass through the OpenFlow switches.The limited bandwidth resources confine the data traffic which can pass through the network links.A concept of resource preference is suggested based on traffic characteristics, and batch routing strategy is proposed to process multiple flow requests simultaneously.We first model and formulate the batch routing optimization problem, and then present a heuristic algorithm called BRP-SA to execute batch routing algorithm with resource preference consideration.Simulation results show that BRP-SA effectively balances the utilization of both flow table and bandwidth resources, and then the network accepts more flow requests.

Cite this article

FANG Qiusheng , HONG Peilin . Batch routing in SDN networks with resource preference consideration[J]. Journal of University of Chinese Academy of Sciences, 2016 , 33(4) : 554 -561 . DOI: 10.7523/j.issn.2095-6134.2016.04.018

References

[1] McKeown N, Anderson T, Balakrishnan H, et al.OpenFlow: enabling innovation in campus networks[J].ACM SIGCOMM Computer Communication Review, 2008, 38(2): 69-74.
[2] Curtis A R, Mogul J C, Tourrilhes J, et al.DevoFlow: scaling flow management for high-performance networks[J].ACM SIGCOMM Computer Communication Review, 2011, 41(4): 254-265.
[3] Huang D Y, Yocum K, Snoeren A C.High-fidelity switch models for software-defined network emulation //Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking.ACM, 2013: 43-48.
[4] Moshref M, Yu M, Govindan R, et al.DREAM: dynamic resource allocation for software-defined measurement[J].ACM SIGCOMM Computer Communication Review, 2015, 44(4): 419-430.
[5] Cohen R, Lewin-Eytan L, Naor J S, et al.On the effect of forwarding table size on SDN network utilization //INFOCOM, 2014 Proceedings IEEE.IEEE, 2014: 1 734-1 742.
[6] Luo S, Yu H, Li L.Practical flow table aggregation in SDN[J].Computer Networks, 2015, 92: 72-88.
[7] Feng T, Bi J, Wang K.Joint allocation and scheduling of network resource for multiple control applications in SDN // Network Operations and Management Symposium (NOMS), 2014 IEEE.IEEE, 2014: 1-7.
[8] Zhang J, Xi K, Luo M, et al.Load balancing for multiple traffic matrices using sdn hybrid routing //High Performance Switching and Routing (HPSR), 2014 IEEE 15th International Conference on.IEEE, 2014: 44-49.
[9] Banerjee S, Kannan K.Tag-in-tag: Efficient flow table management in sdn switches //Network and Service Management (CNSM), 2014 10th International Conference on.IEEE, 2014: 109-117.
[10] Trivisonno R, Vaishnavi I, Guerzoni R, et al.Virtual links mapping in future sdn-enabled networks //Future Networks and Services (SDN4FNS), 2013 IEEE SDN for.IEEE, 2013: 1-5.
[11] Sarrar N, Uhlig S, Feldmann A, et al.Leveraging Zipf's law for traffic offloading[J].ACM SIGCOMM Computer Communication Review, 2012, 42(1): 16-22.
[12] Cai Y, Wu B, Zhang X, et al.Flow identification and characteristics mining from internet traffic with hadoop //Computer, Information and Telecommunication Systems (CITS), 2014 International Conference on.IEEE, 2014: 1-5.
[13] Xiao P, Qu W, Qi H, et al.An efficient elephant flow detection with cost-sensitive in SDN //Industrial Networks and Intelligent Systems (INISCom), 2015 1st International Conference on.IEEE, 2015: 24-28.
[14] Hegde S, Koolagudi S G, Bhattacharya S.Scalable and fair forwarding of elephant and mice traffic in software defined networks[J].Computer Networks, 2015, 92: 330-340.
[15] Min G, Wu Y, Wang L, et al.Performance modelling of adaptive routing in hypercubic networks under non-uniform and batch arrival traffic //Local Computer Networks, 2007.32nd IEEE Conference on.IEEE, 2007: 583-590.
[16] A Allalouf M, Shavitt Y.Centralized and distributed algorithms for routing and weighted max-min fair bandwidth allocation[J].Networking, IEEE/ACM Transactions on, 2008, 16(5): 1 015-1 024.
[17] Barnhart C, Hane C A, Vance P H.Using branch-and-price-and-cut to solve origin-destination integer multicommodity flow problems[J].Operations Research, 2000, 48(2): 318-326.
[18] Chowdhury N M, Rahman M R, Boutaba R.Virtual network embedding with coordinated node and link mapping //INFOCOM 2009, IEEE.IEEE, 2009: 783-791.
[19] Yang X Q, Mees A I, Campbell K.Simulated annealing and penalty methods for binary multicommodity flow problems, Progress in Optimization[M].New York: Springer US, 2000: 93-105.
[20] Ganesh A, Massoulié L, Towsley D.The effect of network topology on the spread of epidemics //INFOCOM 2005.24th Annual Joint Conference of the IEEE Computer and Communications Societies.Proceedings IEEE.IEEE, 2005, 2: 1 455-1 466.
[21] Benson T, Akella A, Maltz D A.Network traffic characteristics of data centers in the wild //Proceedings of the 10th ACM SIGCOMM conference on Internet measurement.ACM, 2010: 267-280.
[22] Hardy G H, Littlewood J E, Pólya G.Inequalities[M].Cambridge: Cambridge university press, 1952.

Outlines

/