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研究生:陳昱廷
研究生(外文):Yu-TingChen
論文名稱:在物聯網環境中具有調適排程概念的軟體定義網路架構
論文名稱(外文):Software Defined Networking Architecture with Adaptive Scheduling Concept In Internet of Thing Environment
指導教授:蘇銓清
指導教授(外文):Chuan-Ching Sue
學位類別:碩士
校院名稱:國立成功大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:49
中文關鍵詞:物聯網自適應排程基因演算法形式化方法
外文關鍵詞:IoTAdaptive SchedulingGenetic AlgorithmFormal Method
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隨著物聯網的蓬勃發展,延伸出許多問題,舉例來說物聯網廣泛的在多個不同的子網路中佈署,而其中使用不同的無線通信方式極其異構,要如何將這些子網路有效的整合成一個無縫的通信平台;還有在動態環境中管理這些開放、地理上分散的異構網路是過去幾年的主要研究課題。
其中一種被廣為使用的方法為軟體定義網路的架構,透過中心化的方式將拓樸上的資訊彙整以計算出全域的最佳路由流,而有別於傳統上軟體定義網路大多架構在Data Center Network這種具有高速通訊且單一的網路,我們發現有過去的研究嘗試將軟體定義網路方式架構在基礎設施尚不完善且具有高度異構的自發網路(Spontaneous Network),使得自發網路在多跳異構節點分派封包的基礎之上有能夠考慮應用層面的QoS能力,並且提出一種優先權的機制強化特定應用占用網路資源的概念。
但是在該研究中,雖然有考慮在單一鏈路上做優先權在網路資源占用時間的分配,但沒有考慮在網路的拓樸上有機會能夠選擇另外路徑的可能,如果只做到時間上的分配而路徑由本地端自發的產生,則有很大的可能是只有單一的應用流可以取得較好的QoS,而壓縮到了其他應用可以選擇其他次佳路由的可能。
本文將繼續過往研究的架構,加入路由流排程(flow routing scheduling)的概念,使用基因演算法幫助controller解決多限制的路徑選擇這個NP-complete的難題,在其中透過Formal Method合理的預估網路資源的負載,並只在過載的鏈路啟用分配網路資源占用時間的機制,使得我們的軟體定義網路架構能夠在密集與稀疏的網路拓樸環境當中自我調適出最佳化排程的策略。
With the development of the Internet of Things, many problems have been extended. For example, the Internet of Things is widely deployed in multiple different sub-networks, and the use of different wireless communication methods is extremely heterogeneous. How to effective integration these sub-networks into a seamless communication platform; Man-aging geographically dispersed heterogeneous networks in a dynamic environment has been a major research in the past few years.
One of the used methods is the SDN (Software Defined Networking Architecture), which aggregates topological information through a Centralized View to Calculate the best route flow for the entire domain, but deploying SDN in IoT is different from in tradition environment. We have found that past research attempts to build a SDN method on a Spontaneous Network with infrastructure-less and a highly heterogeneous network, enable consider application-level QoS capabilities on the basis of multi-hop heterogeneous nodes dispatching packets, and proposes a priority mechanism to strengthen the concept of specific applications occupying network resources.
However, in this study, although consideration was given to assigning priority to network resource occupation time on a single path, it did not consider the possibility of having the opportunity to choose other paths in the network topology. If only time schedule is achieved and the path is spontaneously generated by the local end, it is very likely that only a single application flow can achieve better QoS, and it is compressed to the possibility that other applications can choose other sub-optimal routes.
This article will continue the architecture of the previous research and add the concept of flow routing scheduling, use Genetic Algorithm to help SDN controller solve hte NP-Complete problem of multi-restricted path selection, in which the Formal Method is used to reasonably estimate the load of network resources, and the mechanism of allocating network resource occupation time is activated only on Overloaded links, enabling our SDN architecture to self-adjust to optimal scheduling strategies in dense and sparse network topology environments.
Acknowledgements VIII
List of Tables X
List of Figures XI
1 Introduction 1
2 Background and Related Work 4
2.1 Spontaneous Networking 4
2.2 Software-Defined Networking 5
2.2.1 SDN Architecture 5
2.2.2 OpenFlow Protocol 5
2.3 SDN for Intenet of Things 7
2.4 Genetic Algorithm 7
2.5 Motivation 8
3 System Architecture 10
3.1 Real Ad hoc Multi-hop Peer-to-peer (RAMP) Middleware 10
3.1.1 RAMP Core Layer 11
3.1.2 RAMP Service Layer 14
3.1.3 SDN Client 16
3.1.4 SDN Controller 20
3.2 Formal Method 23
3.3 Flow Scheduling 28
3.3.1 Definition of chromosome 28
3.3.2 Genetic Algorithm 29
4 Implement and Evaluation 34
4.1 Time Complexity Analysis 34
4.2 Experiment Setup 36
4.3 Evaluation 41
5 Conclusion and Future Work 45
6 Reference 46
7 Appendix 49
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