Modeling, Design and Optimization of Multi-Layer Telecommunications Networks 分層式通訊網絡的建模，設計與優化
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CITY UNIVERSITY OF HONG KONG 香/Î市'x Modeling, Design and Optimization of Multi-layer Telecommunications Networks 分d式通訊²a的ú!，設計與*化 Submitted to Department of Electronic Engineering ûP工程û in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy 哲xZëxM by PENG YU m宇 March 2016 二零一mt三月 Abstract Traffic carried by telecommunication networks has experienced explosive growth regarding both volume and dynamics due to the increasing usage of the Internet all around the world. Emerging new applications and new technologies lead telecom- munication networks to a heterogeneous multi-layer multi-technology structure over which multiple services can be provided. For many decades, the design and analysis of telecommunication networks were based on tools developed for the telephone systems, namely, the Erlang formulae. Given the size, complexity and evolving pace of today’s telecommunication networks as well as growing concerns about energy consumption, the original Erlang formulae are no longer adequate. Thus, there is a need for new scalable methodologies to achieve cost effective network designs and operations. The focus of this thesis is modeling, design and performance analysis of multi- layer and multi-technology networks. The primary objective is to find robust and cost- effective design and dimensioning methodologies of multi-layer communications networks. In this thesis, we propose a near-optimal analytical solution to multi-layer network design problem, which applies to an arbitrary number of layered transport technologies, and realistically sized networks with stochastic traffic models. This solution decides virtual network topologies, link capacity assignments with near optimal choices of routing paths and transport technologies so that total network installation and operation cost are minimized. The key novelty of this solution is the inclusion of stochastic traffic models in a multi-layer network optimization. The incorporation of layering and PPBP traffic introduces a complexity, which cannot readily be managed in the framework of the traditional network optimization methodologies. Fortunately, a radical simplification ensues by adopting the shortest path routing as the overall design philosophy. The optimization algorithm then becomes an iterative application of the shortest path routing together with link-by- link dimensioning, in all layers. There are interesting findings presented in this thesis, which are observed from the empirical results of our algorithm on a range of networks including the 100-node “CORONET” network. Furthermore, a new ILP solution is proposed for the multi-layer network design problem as a benchmark for our heuristic algorithm. Cost model is another fundamental element in multi-layer network design prob- lems. A correct and detailed accounting of cost model is also the foundation for networking research in the areas of network optimization, network evolution, net- work design algorithms, network performance evaluation and network management. In this thesis, we propose an idea of using the principle similar to double entry bookkeeping in general accountancy to validate network cost models and thereby the implementation of network design optimization. The key validation technique is to ensure that total network cost calculated from traffic is the same as total network cost calculated by summing the cost of devices and equipment. We show that this principle theoretically justifies pricing based optimization. We also demonstrate how double entry bookkeeping ensures correct results and how optimization fails because of invalid cost, by using the heuristic we proposed as an example. Then we further extend the cost model study to cost error sensitivity analysis of the shortest path routing algorithm. We show that shortest path routing algorithm is an efficient design principle for multi-layer networks, but it can lead to bad designs if the cost models are inaccurate. iv CITY UNIVERSITY OF HONG KONG Qualifying Panel and Examination Panel Surname: PENG First Name: Yu Degree: PhD College/Department: Department of Electronic Engineering The Qualifying Panel of the above student is composed of: Supervisor(s) Prof. ZUKERMAN Moshe Department of Electronic Engineering City University of Hong Kong Qualifying Panel Member(s) Dr. CHAN Chi Hung Sammy Department of Electronic Engineering City University of Hong Kong Dr. WONG Wing Ming Eric Department of Electronic Engineering City University of Hong Kong This thesis has been examined and approved by the following examiners: Dr. CHAN Chi Hung Sammy Department of Electronic Engineering City University of Hong Kong Dr. DAI Lin Department of Electronic Engineering City University of Hong Kong Prof. ZUKERMAN Moshe Department of Electronic Engineering City University of Hong Kong Prof. Tak-Shing Peter YUM Department of Information Engineering The Chinese University of Hong Kong This thesis is dedicated to my parents, for their endless love, support and encouragement. Acknowledgements I am using this opportunity to express my gratitude to everyone who supported me throughout my Ph.D. degree pursuing. Foremost, I would like to express my sincere gratitude to my supervisor Prof. Moshe ZUKERMAN, for continuous support of my Ph.D. study and research with his patience. Without his inspiration, mentorship, and continuous encouragement, I could not have finished my Ph.D. program and this thesis. I wish to express my gratitude to Prof. Ronald G. Addie, for his continuous inspiration, support, advice and provision in the software development and data analysis of my research work. I would like to thank all my Ph.D. panel members Dr. DAI Lin, Dr. CHAN Chi Hung Sammy and Prof. Tak-Shing Peter YUM for the helpful comments. I am especially grateful to Dr. DAI Lin for her detailed feedback. I wish to also thank Dr. CHAN Chi Hung Sammy and Dr. WONG Wing Ming Eric for serving on my Ph.D. committee. In addition, special thanks are due to Dr. Zvi ROSBERG for the opportunity to contribute to the work on job assignment on server farms and for his guidance, patience and feedback in this project. Finally, and always, I thank my parents for all the supports and encouragements they have given me over these years. The work described in this thesis was supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China [CityU 123012] and [CityU 124709]. Table of Contents List of Figures xv List of Tables xix List of Acronyms xxi 1 Introduction1 1.1 Background and Motivations . .1 1.2 Thesis Outline . .3 1.3 List of Publications . .5 2 Telecommunications Networks: Past, Present and Future7 3 Network Architecture: Multi-layer and Multi-technology 13 3.1 OSI Model . 14 3.2 TCP/IP Reference Model . 15 3.3 The Multi-layer Model . 16 3.3.1 Enabling Technologies and Protocols . 18 3.3.2 IP/MPLS over ATM over SONET/SDH . 20 3.3.3 IP/MPLS over SONET/SDH . 21 3.3.4 IP/MPLS over Ethernet . 22 3.3.5 IP/MPLS over OTN/WDM . 22 Table of Contents 4 Multi-layer Network Modeling 25 4.1 Traffic Models . 26 4.1.1 Poisson Process . 26 4.1.2 Poisson Pareto Burst Process (PPBP) . 28 4.2 Statistical Multiplexing and Traffic Grooming . 30 4.3 Cost Model . 32 4.3.1 Minimum Cost Routing . 33 4.3.2 Cost Optimal Routing . 33 4.4 Network Design Problem Modeling . 34 4.5 Literature Review . 40 4.6 Network Mark-up Language (Netml) . 43 4.6.1 Main Features . 44 4.6.2 Current Functions . 44 4.6.3 Example . 45 5 Cost Effective Design of Multi-layer, Multi-technologies Network with Long Range Dependent Traffic 47 5.1 Introduction . 48 5.1.1 Novelty and Contributions . 52 5.2 Problem Description . 56 5.2.1 Preliminaries and Notations . 57 5.2.2 Problem Formulation . 59 5.2.3 Optimization Strategy . 61 5.3 Mathematical Formulation . 61 5.3.1 The ILP Formulation . 62 5.3.2 Comparison between the ILP and the link-path coefficient ILP 65 5.4 Solution: A Multilayer“Market” Algorithm (MMA) . 66 xii Table of Contents 5.4.1 The Selection and Testing of Candidate Virtual Permanent Links . 69 5.4.2 Fixed Point Stopping Criteria . 72 5.4.3 Modeling Choice of Technologies . 73 5.5 Implementation and Numerical Results . 74 5.5.1 Six-node Network Results . 74 5.5.2 Practical Networks Results . 78 5.5.3 Network Evolution Prediction . 78 5.5.4 Flow-size Dependent Routing . 79 5.5.5 Threshold Optimization . 81 5.5.6 Running Time of the Heuristic Algorithm . 82 5.5.7 Further Validation . 83 5.6 Summary . 83 6 Shortest Path Routing in Multi-layered Networks 85 6.1 Introduction . 86 6.2 Shortest Path in Layered Network Design . 88 6.2.1 Link Cost Instability . 89 6.2.2 Power Law Traffic . 90 6.3 Example Networks and Results . 90 6.3.1 Link-cost Inaccuracy . 93 6.3.2 The Effect of Link-cost Errors . 96 6.4 Summary . 99 7 Cost Validation in Multi-layer Network Architecture and Design 101 7.1 Introduction . 102 7.1.1 Network Cost Models . 102 7.1.2 Cost Models and Network Optimization . 103 7.2 Network Cost Models . 105 xiii Table of Contents 7.2.1 Sharing . 106 7.2.2 Aggregation . 107 7.2.3 Discounting . 107 7.2.4 Transfer between Layers . 108 7.3 Validation of Network Costs . 108 7.3.1 Validity of Price-based Optimisation Algorithms . 109 7.3.2 Spare Capacity and Investment Clawback . 110 7.4 The MMA and Its Cost Validation . 111 7.5 Experiments . 115 7.6 Summary . 118 8 Contributions, Conclusions and Future Work 119 References 123 Appendix A Parameter Tables for Netml Experiments 135 xiv List of Figures 2.1 Global IP traffic per month forcasted by Cisco. .9 3.1 Mapping between the OSI reference model, TCP/IP model and next- generation multi-layer model.