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研究生: 吳昇蓉
Wu, Sheng Jung
論文名稱: 基於軟體定義網路之應用程式網路流量分配管理系統設計與研製
Bandwidth Allocation and Management of Applications in Slicing Networks Toward SDN on vCPE Framework
指導教授: 黃能富
Huang, Nen Fu
口試委員: 石維寬
Shih, Wei Kuan
陳俊良
Chen, Jiann Liang
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 50
中文關鍵詞: 服務品質管理軟體定義網路網路流量分配流量辨識
外文關鍵詞: Ryu, Flow Classification
相關次數: 點閱:2下載:0
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  • 現今有越來越多的網路應用出現,如線上遊戲、網路串流、線上會議等,如此運行在網路上的流量越來越大,越來越複雜,因此如何保證網路品質及網路管理,成為了十分重要的議題。
    過去,在傳統網路之上,為了滿足如此以上需求,學者提出了兩個主要的解決方法,Integrated service(IntServe)使用Resource Reservation Protocol (RSVP)來達到封包區別以提供對應的頻寬及路由;Differentiate service(Diffserv) 則對封包分類並加入標記,來對應不同的網路品質。然而,這兩種方法皆無法很成功的達到需求,因為傳統網路為分散式的架構,無法做的快速及一致性地配置,操作及管理。
    而在過去的幾年來,美國史丹佛大學提出了一個新的網路架構,名為軟體定義網路,在此網路架構底下,他將控制層和傳輸層做分開,使得網路管理更加的便利,於是,我將其導入其架構,並選擇日本NTT公司所設計的RYU,以OpenFlow Protocols為基礎的一個Controller platform,我的目標為提供一個以flow-based的網路管理機制,其特色包含動態路由轉換機制,頻寬分配機制,網路資源分配等,在有限的資源底下,提供使用者最佳的網路品質,主要特色詳細介紹如下列所示。透過網路資源分配管理機制,為提高QoS頻寬設定效率及分配適當,希望可以加入網路切片(Network slicing)的概念,將網路上的連結及節點做分群,並利用偵測擁塞方法,偵測網路發生狀況,當資源不足,利用我們針對頻寬的分配設計了一套機制,結合Collaborative Filtering Algorithm及Flow Classification,並在最後加入動態路由路經轉換機制,以保持並達到資源分配最佳化,並可對不同網路層面的流量做管理。
    最後,我們將此系統結合了vCPE的系統並設計了使用者介面,除了達到網路虛擬化外,也讓網路管理者更加容易操作及監控網路狀況。


    In recent decades, the demand for network services has grown rapidly. Applications and users make the network more complicated than it ever was. Services that require high bandwidth and/or low latency are greatly susceptible to the effects of traffic congestion. A novel network architecture referred to as Software Defined Networking (SDN) proposed in 2009 decouples the control plane from the data plane of switches, having one centralized controller for the network so that network managers could have chances to control and manage the network as desired.
    This paper presents a quality-of-service (QoS) management system integrated with a flow classification engine. This makes it possible for network managers to divide hosts and resources into several groups, for which the system identifies the optimal route with minimum costs, based on real-time monitored statistics and a pre-determined cost model. It also enables the alteration of routing paths in situations of traffic congestion. Finally, we adopted the concept of Collaborative Filtering for usage prediction and bandwidth allocation. Experiment results demonstrate the efficacy of the proposed algorithm and system architecture in providing a QoS with minimal overhead and precise bandwidth management.
    Finally, for achieving network virtualization and easy management, we also integrate the QoS system with a novel framework which realize the vCPE concept through SDN technology. Users or enterprise could just subscribe the QoS services and set the parameters which is needed and monitors the network status in real time via the web-based user interface we provide.

    Abstract II Figure List VI Table List VIII Chapter 1 Introduction 1 Chapter 2 Related Works 4 2.1 Software-Defined Networking 4 2.2 OpenFlow Protocols 6 2.3 Virtual Consumer Premises Equipment 8 2.4 Flow Classification Platform 9 2.5 QoS Technologies in Legacy Network 11 2.5.1 Integrated Services (IntSrev) 11 2.5.2 Differentiated services (DiffServ) 12 2.6 Recent research of Openflow-based QoS Systems 13 Chapter 3 System Design and Implementation 17 3.1 System Core Design 17 3.1.1 Allocation and Management of Network Resources 18 3.1.2 Congestion Monitoring 20 3.1.3 Adjustment of QoS Routing Paths 21 3.1.4 Traffic Prediction and bandwidth distribution 21 3.2 System implementation 24 3.2.1 Ryu Controller 24 3.2.2 Flow Classification Platform 25 3.2.3 Monitoring 25 3.2.4 Initial Setting 27 3.2.5 Packet Handling 28 3.2.6 Bandwidth Control 29 Chapter 4 Experimental Results 33 4.1 Traffic Prediction 33 4.2 Congestion Monitoring 35 4.3 Network Resource Grouping management 36 4.4 Dynamic Bandwidth Allocation 38 4.5 Rate-Limited for Host and Protocol 40 4.6 QoS Routing 41 4.6.1 Flow completion Time 42 4.6.2 PacketIN – choose the least-cost path 43 4.6.3 Congestion –Dynamic Path Adjustment, changing the route 46 Chapter 5 Conclusion and Future Works 49 Reference i

    [1] H. J. Burkhardt and T. H. Krecioch, "Standards for the ISO — Reference model for open systems interconnection," Microprocessing and Microprogramming, vol. 9, pp. 237-244, 1982/04/01 1982.
    [2] C. Kale and T. Socolofsky. TCP/IP tutorial [Online]. Available: http://tools.ietf.org/html/rfc1180
    [3] D. Clark, B. Braden, and S. Shenker, "Integrated Service in the Internet Architecture: An Overview," 1994.
    [4] S. Blake, D. Black, M. Carlson, E. Davies, Z. Wang, and W. Weiss, "An architecture for differentiated services," 1998.
    [5] D. O. Awduche and J. Agogbua, "Requirements for traffic engineering over MPLS," 1999.
    [6] M. Casado, M. J. Freedman, J. Pettit, J. Luo, N. McKeown, and S. Shenker, "Ethane: taking control of the enterprise," SIGCOMM Comput. Commun. Rev., vol. 37, pp. 1-12, 2007.
    [7] Ryu[Online]. Available: https://osrg.github.io/ryu/
    [8] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, et al., "OpenFlow: enabling innovation in campus networks," SIGCOMM Comput. Commun. Rev., vol. 38, pp. 69-74, 2008.
    [9] N. Operators, "Network Functions Virtualization, An Introduction, Benefits, Enablers, Challenges and Call for Action," in SDN and OpenFlow SDN and OpenFlow World Congress, 2012.
    [10] SDN Structure[Online]. Available: https://www.sdxcentral.com/sdn/resources/inside-sdn-architecture/
    [11] OpenFlow[Online] Available: http://archive.openflow.org/
    [12] OpenNaaS White paper. Available: https://ec.europa.eu/digital-agenda/events/cf/h2020-future-internet-call-2015/document.cfm?doc_id=21348
    [13] NFV virtualisation of the home environment Available: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6940493&queryText=NFV%20virtualiza-on%20of%20the%20home%20environment&newsearch=true
    [14] Ericsson. Available: http://www.ericsson.com/res/docs/2014/virtual-cpe-and-software-defined-networking.pdf
    [15] NEC's vCPE Solutions. Available: http://www.nec.com/en/global/solutions/tcs/vcpe/
    [16] N.-F. Huang, G.-Y. Jai, H.-C. Chao, Y.-J. Tzang, and H.-Y. Chang, "Application traffic classification at the early stage by characterizing application rounds," Inf. Sci., vol. 232, pp. 130-142, 2013.
    [17] C. Chi-Sung, "Realization of Application Identification System Based on Statistical Signatures," Institute of Communications Engineering, National Tsing-Hua University, 2015.
    [18] Z. A. Qazi, J. Lee, T. Jin, G. Bellala, M. Arndt, and G. Noubir, "Application-awareness in SDN," presented at the Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM, Hong Kong, China, 2013.
    [19] N. Hyunwoo, K. Kyung-Hwa, K. Jong Yul, and H. Schulzrinne, "Towards QoE-aware video streaming using SDN," in Global Communications Conference (GLOBECOM), 2014 IEEE, 2014, pp. 1317-1322.
    [20] D. Adami, L. Donatini, S. Giordano, and M. Pagano, "A network control application enabling Software-Defined Quality of Service," in Communications (ICC), 2015 IEEE International Conference on, 2015, pp. 6074-6079.
    [21] R. Sherwood, G. Gibb, K.-K. Yap, G. Appenzeller, M. Casado, N. McKeown, et al., "Can the production network be the testbed?," presented at the Proceedings of the 9th USENIX conference on Operating systems design and implementation, Vancouver, BC, Canada, 2010.
    [22] H. E. Egilmez, S. T. Dane, K. T. Bagci, and A. M. Tekalp, "OpenQoS: An OpenFlow controller design for multimedia delivery with end-to-end Quality of Service over Software-Defined Networks," in Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific, 2012, pp. 1-8.
    [23] S. Kulkarni, R. Sharma, P. Sharan, and R. B. R. Gowd, "New dynamic QoS routing algorithm for optical networks based on MPLS with delay and Bandwidth as constraints," in Optical Engineering (ICOE), 2012 International Conference on, 2012, pp. 1-6.
    [24] H. E. Egilmez, S. Civanlar, and A. M. Tekalp, "An Optimization Framework for QoS-Enabled Adaptive Video Streaming Over OpenFlow Networks," Multimedia, IEEE Transactions on, vol. 15, pp. 710-715, 2013.
    [25] L. Kailong, G. Wei, Z. Wenyu, W. Yuan, L. Chengjun, and H. Weisheng, "QoE-based bandwidth allocation with SDN in FTTH networks," in Network Operations and Management Symposium (NOMS), 2014 IEEE, 2014, pp. 1-8.
    [26] A. Lara, A. Kolasani, and B. Ramamurthy, "Network Innovation using OpenFlow: A Survey," IEEE Communications Surveys & Tutorials, vol. 16, pp. 493-512, 2014.
    [27] S. S. W. Lee, L. Kuang-Yi, C. Kwan-Yee, C. Yao-Chuan, and L. Guan-Hao, "Design of bandwidth guaranteed OpenFlow virtual networks using robust optimization," in Global Communications Conference (GLOBECOM), 2014 IEEE, 2014, pp. 1916-1922.
    [28] S. Tomovic, N. Prasad, and I. Radusinovic, "SDN control framework for QoS provisioning," in Telecommunications Forum Telfor (TELFOR), 2014 22nd, 2014, pp. 111-114.
    [29] H. Nen-Fu, I. J. Liao, L. Hung-Wei, W. Sheng-Jung, and C. Chi-Sung, "A dynamic QoS management system with flow classification platform for software-defined networks," in Ubi-Media Computing (UMEDIA), 2015 8th International Conference on, 2015, pp. 72-77.
    [30] Mininet[Online]. Available: http://mininet.org/
    [31] Pica8 Switch[Online]. Available: http://www.pica8.com/
    [32] "IEEE Draft Standard for Local and Metropolitan Area Networks: Media Access Control (MAC) Bridges (Revision of IEEE Std 802.1D -1998 Incorporating IEEE Std 802.1T -2001 IEEE Std 802.1W -2001) (Replaced by 802.1D-2004)," IEEE Std P802.1D/D4, p. 1, 2003.
    [33] "IEEE Standard for Local and Metropolitan Area Networks---Virtual Bridged Local Area Networks---Amendment 4: Provider Bridges," IEEE Std 802.1ad-2005 (Amendment to IEEE Std 802.1Q-2005), pp. 1-74, 2006.
    [34] X. Su and T. M. Khoshgoftaar, "A Survey of Collaborative Filtering Techniques," Advances in Artificial Intelligence, vol. 2009, p. 19, 2009.
    [35] Open vSwitch[Online]. Available: http://openvswitch.org/
    [36] R. J. Hyndman and A. B. Koehler, "Another look at measures of forecast accuracy," International Journal of Forecasting, vol. 22, pp. 679-688, 10// 2006.
    [37] iPerf[Online]. Available: https://iperf.fr/
    [38] NOXRepo.org [Online]. Available: http://www.noxrepo.org/
    [39] Floodlight[Online]. Available: http://www.projectfloodlight.org/floodlight/

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