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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/111389


    Title: 以SDN為基礎之具服務品質感知的智慧家庭頻寬管理架構
    SDN based QoS aware bandwidth management framework for smart homes
    Authors: 林建廷
    Lin, Jian Ting
    Contributors: 張宏慶
    Jang, Hung Chin
    林建廷
    Lin, Jian Ting
    Keywords: 物聯網
    智慧家庭
    頻寬分配
    軟體定義網路
    Internet of things
    Smart home
    Bandwidth allocation
    Software defined networking
    Date: 2017
    Issue Date: 2017-07-24 12:19:27 (UTC+8)
    Abstract: 隨著智慧家庭技術及物聯網的裝置大幅度地成長,智慧家庭的網路流量亦隨之升高。當大量成長的智慧家庭流量造成網路壅塞時,可能使緊急服務的警告機制失效,或是造成某些應用服務品質低劣而不堪使用。這些問題恐阻礙智慧家庭未來的發展性。

    為改善上述問題,本文提出創新的物聯網智慧家庭頻寬配置管理架構。以ISP業者管理數以千計的物聯網智慧家庭為情境,針對智慧家庭多樣化的應用服務,利用具前瞻性的軟體定義網路,提供ISP業者對智慧家庭外部網路頻寬做最佳化的配置。

    本研究依改良後的3GPP LTE QoS Class Identifier (QCI),分類智慧家庭的服務,並考量服務的優先權及延遲程度,提出BASH演算法。透過本研究,ISP業者能依定義好的服務類別,將匯集後的智慧家庭服務流量藉由配置訊務流(traffic flow)的權重,計算出不同服務的最佳頻寬分配量,達到提升QoS及使用者QoE的目的。

    為確認本論文所提出之方法的有效性,實驗設計是利用Linux伺服器架設OpenvSwitch、Ryu控制器及Mininet模擬器,建構SDN網路環境。實驗結果顯示,本研究所提出的BASH與ISP所用的傳統頻寬分配方法相比,能有效提高30%的throughput,降低159%的delay time及967%的 jitter time。
    With the increasing number of IoT (Internet of Things) devices and advance of smart home technology, the network traffic of smart home is also raising rapidly. When network congestion occurs due to massive traffic, some emergent alert mechanisms might become invalid or cause some application services performance degraded. All kinds of these will dramatically hamper the future development of smart homes.

    In order to resolve these problems, we propose an innovative bandwidth allocation smart home management framework for IoT enabled smart homes. The application scope of this research assumes a scenario that an ISP (Internet Service Provider) should support thousands of IoT enabled smart homes for a variety of services. The proposed bandwidth allocation framework is based on the promising software defined networking (SDN) architecture and is responsible for optimizing bandwidth allocation on external Internet traffic.

    We modify the 3GPP LTE QoS Class Identifier (QCI) to adaptive to the services suitable for smart homes. The proposed bandwidth allocation smart home (BASH) algorithm considers service priority and delay at the same time. With this framework, ISP is able to optimize bandwidth allocation by aggregating thousands of classified services of smart homes and thus effectively enhance Quality of Service (QoS) and user experience (QoE).

    In order to verify the proposed methods, we implement a SDN environment by using Linux Ubuntu servers with Mininet, Open vSwitch and Ryu controller. The experiment results show that BASH outperforms ISP traditional method in increasing the throughput by 30%, reducing delay and jitter by 159% and 967%, respectively.
    Reference: [1] Alaitz Mendiola; Jasone Astorga; Eduardo Jacob; Kostas Stamos; Artur Juszczyk; Krzysztof Dombek; Jovana Vuleta-Radoičić; Jordi Ortiz, "Multi-domain Bandwidth on Demand service provisioning using SDN", Proc. 2016 IEEE NetSoft Conference and Workshops (NetSoft)., pp. 353-354.
    [2] Alexander Craig; Biswajit Nandy; Ioannis Lambadaris; Peter Ashwood-Smith,"Load balancing for multicast traffic in SDN using real-time link cost modification", Proc 2015 IEEE International Conference on Communications (ICC)., pp. 5789 – 5795.
    [3] Alon Atary; Anat Bremler-Barr,"Efficient Round-Trip Time monitoring in OpenFlow networks", Proc. IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications., pp. 1-9.
    [4] Difference between SDN and Traditional Architecture, http://www.geego.com.tw
    [5] Elif Bozkaya; Berk Canberk, "QoE-based Flow Management in Software Defined Vehicular Networks", Proc. 2015 IEEE Globecom Workshops (GC Wkshps)., pp. 1-6.
    [6] Gi-Hoon Jung; Hwa-Young Chae; Soon-Ju Kang,"Real-Time Bandwidth Management Middleware for Multi-session Isochronous Streaming Service in the IEEE1394-based Home Network" Proc. IEEE Transactions on Consumer Electronics., pp. 461-469 2009
    [7] Iperf, https://iperf.fr/, retrieved date: 2016/09/25
    [8] Ke Xu; Xiaoliang Wang; Wei Wei; Houbing Song; Bo Mao,"Toward Software Defined Smart Home", Proc. IEEE Communications Magazine., pp 116-122, Volume: 54, Issue: 5 2016.
    [9] Linux Ubuntu, https://www.ubuntu.com/, retrieved date: 2016/08/28.
    [10] M. Belyaev; S. Gaivoronski,"Towards Load Balancing in SDN-Networks During DDoS-attacks" Proc. 2014 International Science and Technology Conference (Modern Networking Technologies) (MoNeTeC)., pp 1-6.
    [11] Mininet, http://mininet.org/, retrieved date: 2016/08/30.
    [12] Network Operating System, https://ryu.readthedocs.io/en/latest/, retrieved date: 2016/08/28.
    [13] Open vSwitch, http://openvswitch.org/,retrieved date: 2016/09/25.
    [14] OpenFlow Switch Specification, https://www.opennetworking.org/images/stories/downloads/sdn-resources/onf-specifications/openflow/openflow-spec-v1.3.0.pdf,retrieved date: 2016/08/26
    [15] Python, https://www.python.org/,retrieved date: 2016/09/25
    [16] Ryoma Yasunaga; Yu Nakayama; Takeaki Mochida; Yasutaka Kimura; Tomoaki Yoshida; Ken-ichi Suzuki, "Optimal Load Balancing Method for Symmetrically Routed Hybrid SDN Networks" Proc. 2015 21st Asia-Pacific Conference on Communications (APCC)., pp. 234-238
    [17] Ryu Book, https://osrg.github.io/ryu-book/en/html/rest_qos.html,retrieved date: 2016/09/25
    [18] Ryu, https://osrg.github.io/ryu/, retrieved date: 2016/09/25.
    [19] Ryu`s Architecture, http://www.ntt.co.jp/index_e.html,retrieved date: 2016/09/25.
    [20] Ryu`s Components, https://osrg.github.io/ryu/slides/ONS2013-april-ryu-intro.pdf, retrieved date: 2016/09/25.
    [21] SDN Architecture, http://opennetsummit.org/archives/apr12/site/why.html,retrieved date: 2016/09/25.
    [22] SDN three tier Architecture, https://www.sdxcentral.com/sdn/definitions/inside-sdn-architecture/, retrieved date: 2016/09/25.
    [23] SDN Instructions & Actions, http://flowgrammable.org/sdn/openflow/actions/,retrieved date: 2016/09/25.
    [24] Seungbeom Song; Jaiyong Lee; Kyuho Son; Hangyong Jung; Jihoon Lee, "A Congestion Avoidance Algorithm in SDN Environment", Proc. 2016 International Conference on Information Networking (ICOIN)., pp. 420-423.
    [25] Shiwei Wang; Xiaoling Wu; Hainan Chen; Yanwen Wang; Daiping Li, "An Optimal Slicing Strategy for SDN based Smart Home Network", Proc. International Conference on Smart Computing., pp. 118-122 2014
    [26] SmartHome for TWM Broadband, http://www.twmbroadband.com/T01/content_4_0_1057.html, retrieved date: 2016/09/25.
    [27] SmartHome for Chunghwa Telecom, http://www.cht.com.tw/personal/smart-home.html, retrieved date: 2016/09/25.
    [28] SmartHome for Fareastone, http://smarthome.fetnet.net/smarthome/, retrieved date: 2016/09/25.
    [29] Srinivasan Dwarakanathan; Len Bass; Liming Zhu, "Cloud Application HA using SDN to ensure QoS", Proc. IEEE 8th International Conference on Cloud Computing., pp.1003 - 1007 2015.
    [30] Virtualbox, https://www.virtualbox.org/,retrieved date: 2016/09/25.
    [31] Vmware, http://www.vmware.com,retrieved date: 2016/09/25.
    [32] WANG Yong, TAO Xiaoling, HE Qian, KUANG Yuwen, "A Dynamic Load Balancing Method of Cloud-Center Based on SDN", Proc China Communications., pp.130-137, 2016.
    [33] Younggi Kim and Younghee Lee, “Automatic Generation of Social Relationships between Internet of Things in Smart Home using SDN-based Home Cloud,” Proc, 2015 29th International Conference on Advanced Information Networking and Applications Workshops (WAINA),” Gwangiu, South Korea, March 24-27, 2015, pp: 662-667.
    [34] Yuanhao Zhou; Mingfa Zhu; Limin Xiao; Li Ruan; Wenbo Duan; Deguo Li; Rui Liu; Mingming Zhu, "A Load Balancing Strategy for SDN Controller based on Distributed Decision" Proc. 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications., pp 851-856
    [35] Northbound and Southbound,http://www.edn.com/design/wireless-networking/4427694/Software-Defined-Networking-in-Mobile--The-Basics, retrieved date: 2016/09/25.
    [36] Smart Home overview,http://www.wareable.com, retrieved date: 2016/09/25
    [37] OpenDaylight, http://sdnhub.org/wp-content/uploads/2013/11/opendaylight_helium.jpg,retrieved date: 2016/09/25.
    [38] Hung-Chin Jang; Chi-Wei Huang; Fu-Ku Yeh, "Design a bandwidth allocation framework for SDN based smart home.", Proc. 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)., pp. 1-6 2016
    [39] Suneth Namal; Ijaz Ahmad; Andrei Gurtov; Mika Ylianttila,"SDN Based Inter-Technology Load Balancing Leveraged by Flow Admission Control" Proc. 2013 IEEE SDN for Future Networks and Services (SDN4FNS)., pp. 1-5.
    [40] Mobile Marketing in US,https://www.npd.com/wps/portal/npd/us/news/press-releases/internet-connected-devices-surpass-half-a-billion-in-u-s-homes-according-to-the-npd-group/, retrieved date: 2016/09/25
    [41] Number of smartphone users, https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/, retrieved date: 2016/09/25
    [42] 王辰佑、林盈達,SDN 標準與測試,國立交通大學資訊工程系,September 15, 2014
    [43] 陳昶禎、 高勝助,以 OpenFlow 實作區域網路管理模組, 國立中興大學資訊科學與工程學系,2014 Conference on Information Technology and Applications in Outlying Islands,pp. 173-180.
    [44] Abdullah Sinan Yildirim, Tolga Girici,"Cloud Technology and Performance Improvement with Intserv over Diffserv for Cloud Computing", Proc. 2014 IEEE International Conference on Future Internet of Things and Cloud., pp 222 – 229.
    [45] Yash Sinha; Siddharth Bhatia; Virendra S Shekhawat; G. S. S. Chalapathi,"MPLS based hybridization in SDN”, Proc. 2017 Fourth International Conference on Software Defined Systems (SDS)., pp 156-161.
    [46] E. Rosen, D. Tappan, G. Fedorkow, Y. Rekhter, D. Farinacci, T. Li, A. Conta,"MPLS Label Stack Encoding", Internet Engineering Task Force, Jan, 2001.
    Description: 碩士
    國立政治大學
    資訊科學系碩士在職專班
    103971001
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103971001
    Data Type: thesis
    Appears in Collections:[資訊科學系碩士在職專班] 學位論文

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