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研究生: 董一志
Tung, Yi-Chih
論文名稱: 智慧家庭聯網之 QoS 資源調配的匯聚策略
Rendezvous Strategy of QoS Provisioning over Intelligent Home Networks
指導教授: 黃文吉
Hwang, Wen-Jyi
學位類別: 博士
Doctor
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2017
畢業學年度: 105
語文別: 英文
論文頁數: 65
中文關鍵詞: QoSGRNNHome NetworkQuality of ServiceChannel allocationPrediction algorithmsBandwidthHome automationAlgorithm design and analysisTrainingNetwork Access Device
英文關鍵詞: QoS, GRNN, Home Network, Quality of Service, Channel allocation, Prediction algorithms, Bandwidth, Home automation, Algorithm design and analysis, Training, Network Access Device
DOI URL: https://doi.org/10.6345/NTNU202202402
論文種類: 學術論文
相關次數: 點閱:108下載:1
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    This dissertation recommends a novel rendezvous strategy for QoS pro- visioning with minimum computing cost over intelligent home networks. Although the usual QoS algorithms such as ow control can be adapted for simplifying the bandwidth allocation, the methods are limited only for local services. The proposed algorithm, termed GRNN QoS (Generalized Regression Neural Network for Quality of Service), is able to provide global home network services while requiring minimum computing complexity. The GRNN QoS is a hybrid combination of ow control and path selection. The ow control is adopted for the adjustment and/or allocation of local bandwidth; whereas, the path selection is used for the collection and/or delivery of local network information to the home networks. With GRNN computation, services provided by the home networks are then global optimality. This algorithm is well-suited for intelligent home networks where the fast QoS provisioning and low computing efforts of the small scale home networks are desired.

    GRNN QoS establishing profiles of user’s various responses to the communication links to different services is the first step for GRNN QoS algorithm. Based on the profiles GRNN QoS can estimate the future feedback to the services from a user. Upon the bandwidth allocations for receiving positive feedback, the algorithm finds a way to minimize the bandwidth usage of the networks. The main advantages of this algorithm are that it quickly adapts to user response and it does not require offline training. This dissertation provides both analytical and numerical analyses to demonstrate the efficacy of said algorithm.

    Contents Acknowledgments i Abstract ii Contents iii List of Figures v List of Tables viii 1 Introduction 1 2 Strategy 5 2.1 Wire and Wireless Relay Network 5 2.2 SON:Self Organizing Network 7 2.3 Path Selection 9 2.4 Flow Control 12 3 GRNN Algorithm 15 General Regression NeuralNetwork 15 4 Proposed Algorithm 18 TheProposed Algorithm: GRNN QoS 18 5 Analytical Analysis 25 GRNN QoS Analytical Analysis 25 6 Experimental Results 31 6.1 Numerical results pertaining to the Proposed Algorithm 31 6.2 More Numerical Examples 37 6.3 Numerical Comparison With the ANN Algorithm 51 6.4 Single-ServiceExperiments 52 7 Conclusion 56 A Home Network Standards 58 A.1 IEEE1905.1 58 A.2 ITU-TG.hn 59 Bibliography 62

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