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Optimization of Proactive Services with Uncertain Predictions Optimization of Proactive Services with Uncertain Predictions A Dissertation Presented by Ran Liu to The Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Northeastern University Boston, Massachusetts October 2020 Contents List of Figures iv List of Tables vi List of Acronyms vii Acknowledgments viii Abstract of the Dissertation ix 1 Introduction 1 1.1 Background . 1 1.2 Proactive Caching and Proactive Computing Technologies . 3 1.2.1 Proactive Caching . 3 1.2.2 Proactive Computing . 7 1.3 Related Work . 9 2 Proactive Caching under Uncertain Predictions 12 2.1 Introduction . 12 2.2 System Model . 14 2.2.1 Network Model . 14 2.2.2 Service Model . 16 2.2.3 Problem Formulation . 19 2.3 Relation between Reactive Scheme and Proactive Schemes . 21 2.4 Threshold-based Proactive Strategy and Markov Chain . 26 2.4.1 Threshold-Based Proactive Strategies . 26 φ 2.4.2 Markov Chain of System under ΨP ..................... 26 2.5 Delay Comparison between UNIFORM and EDF strategies . 37 2.6 Numerical Evaluation . 39 2.6.1 Infinite Prediction Window Scenarios . 40 2.6.2 Finite Prediction Window Scenarios . 43 2.7 Summary . 46 i 3 Delay-Optimal Proactive Strategy under Uncertain Predictions 48 3.1 Introduction . 48 3.2 System Model . 50 3.2.1 Network Model . 50 3.3 System Model . 52 3.3.1 Server Model . 52 3.3.2 Service Model . 54 3.3.3 Problem Formulation . 57 3.4 Relation between Reactive Scheme and Proactive Schemes . 60 3.5 Fixed-Probability (FIXP) Strategy in the Genie-Aided Proactive System . 64 3.5.1 Markov Process of the Genie-Aided System under FIXP(φ) . 65 3.5.2 Recurrence Analysis of the Embedded Markov Chain . 69 3.5.3 Relationship between FIXP(φ) and the two Properties . 73 3.5.4 Delay Analysis of FIXP(φ) Strategies under the Genie-Aided System . 74 3.6 Fixed-Probability (FIXP) Strategy in Realistic Proactive System . 75 3.6.1 The Stochastic Process in the Realistic Proactive System under FIXP(φ) . 75 3.6.2 Analysis on the Approximated Time-invariant Markov Chain . 80 3.6.3 Analysis on the Embedded Chain of the Realistic Proactive System . 82 3.6.4 FIXP Strategies and the Two Properties in Realistic Proactive System . 83 3.6.5 Delay of FIXP strategies in the Realistic Proactive System . 84 3.7 Numerical Evaluation . 84 3.8 Summary . 88 4 SANDIE: SDN-Assisted NDN for Data-Intensive Experiments 90 4.1 Introduction . 92 4.1.1 Large-Scaled Data-Intensive Applications . 92 4.1.2 Named-Data Networking (NDN) Architecture . 94 4.1.3 VIP: Optimized NDN Caching, Forwarding, and Congestion Control . 96 4.2 Data Analysis: LHC network and CMS Workflow . 97 4.2.1 US CMS Network and Workflow . 97 4.2.2 Analysis on CMS Data and Workflow . 101 4.3 Experimental Evaluations . 110 4.3.1 Simulations of the VIP Framework in the Internet2 Topology . 111 4.3.2 Simulations of the VIP Framework with Off-site CMS Workflow . 114 4.4 Modification of VIP Algorithms for SANDIE . 116 4.4.1 Modified Virtual Interest Packet . 117 4.4.2 Modifications on VIP Caching Strategy . 118 4.5 SANDIE Testbed and Implementations . 123 4.5.1 SANDIE Testbed Configuration . 123 4.5.2 Implementation of VIP Framework in Existing NDN Forwarders . 125 4.5.3 Demonstration at SuperComputing 19’ . 129 4.5.4 An Overview of the Latest Progress on the SANDIE Project . 130 4.6 Summary . 131 Bibliography 133 ii A Appendix of Chapter 2 144 A.1 Proof of Proposition 1 . 144 A.2 Proof of Theorem 1 . 145 A.3 Proof of Corollary 1 . 148 A.4 Proof of Proposition 2 . 150 A.5 Proof of Proposition 3 . 152 A.6 Proof of Proposition 4 . 155 A.7 Proof of Lemma 1 . 159 A.8 Proof of Theorem 3 . 162 A.9 Proof of Theorem 4 . 164 A.10 Proof of Corollary 3 . 179 A.11 Proof of Corollary 4 . 180 A.12 Proof of Corollary 5 . 182 B Appendix of Chapter 3 185 B.1 Relationship between the Genie-Aided system and Realistic Proactive system . 185 B.2 Proof of Theorem 5 . 186 B.3 Proof of Corollary 6 . 190 B.4 Proof of Lemma 2 . 191 B.5 Proof of Proposition 8 . 191 B.6 Verification of Theorem 5 under FIXP strategies in Genie-Aided system . 193 B.7 Proof of Proposition 7 . 195 B.8 Proof of Theorem 7 . 198 B.9 Proof of Theorem 8 . 200 B.10 Proof of Proposition 10 . 205 B.11 Verification of Theorem 5 under FIXP strategies in Realistic Proactive system . 206 B.12 Proof of Theorem 10 . 208 iii List of Figures 2.1 Network Model . 15 2.2 Arrival Processes . 15 2.3 Comparison between the Reactive Scheme and the Proactive Scheme . 19 φ s 2.4 Example: Transitions in the proactive system with ΨP , with φ = 2 . 28 2.5 Comparisons among threshold-based methods: λp = 6 . 41 2.6 Comparisons among threshold-based methods: λp = 9:6 . 41 2.7 Comparisons among EDF,UNIFORM and Reactive Schemes: λp = 6 . 42 2.8 Comparisons among EDF,UNIFORM and Reactive Schemes: λp = 9:6 . 42 2.9 Queue Size Evolution Comparisons among Reactive Scheme, EDF strategy and UNIFORM strategy: λp = 6 ............................. 43 2.10 Queue Size Evolution Comparisons among Reactive Scheme, EDF strategy and UNIFORM strategy: λp = 9:6 ............................ 43 2.11 Theoretical Delay Comparison between UNIFORM Strategy and Reactive Scheme 43 2.12 Comparisons among EDF,UNIFORM and Modified-UNIFORM: λp = 6 . 44 2.13 Comparisons among EDF,UNIFORM and Modified-UNIFORM: λp = 9:6 . 44 3.1 Server Model . 52 3.2 Arrival Processes . 52 3.3 Comparisons between reactive and proactive systems . 61 3.4 Embedded Markov Chain of the Markov Process under FIXP Strategies in the Genie-Aided System . 69 3.5 Corresponding 1D Markov Chain Xk ....................... 72 3.6 The transitions of the Realistic Proactivef g System. The corresponding time-invariant transition rates are shown in brackets. 79 3.7 Limiting Fraction of Proactive Services of FIXP Strategies: λp = 6 . 86 3.8 Limiting Fraction of Proactive Services of FIXP Strategies: λp = 9:6 . 86 3.9 Average Delay of FIXP Strategies: λp = 6 ...................... 87 3.10 Average Delay of FIXP Strategies: λp = 9:6 ..................... 87 4.1 On-Site Jobs and Off-Site Jobs in CMS Network . 99 4.2 Distribution of Datablock Size in CMS Workflow of US sites . 103 4.3 Distribution of Datablock Size in CMS Workflow of Caltech Site . 104 iv 4.4 Percentage of Requests Covered by Popular Datablocks: US Sites . 105 4.5 Percentage of Requests Covered by Popular Datablocks: Caltech Site . 106 4.6 Request Counts: Total vs. Popular Datablocks at US Tier-2 Sites . 106 4.7 Zipf Distribution Approximations for Popularity Distributions at US Tier-2 Sites . 107 4.8 File-level Popularity of an Example Datablock . 108 4.9 The Early Internet2 Topology . 111 4.10 Internet2 CMS Topology for Simulation Study . 112 4.11 Delay Performance of VIP Framework in Internet2 Topology . 113 4.12 Average Connection Speed from MIT CMS Site . 115 4.13 Delay Performance of Off-site Workflow in CMS Network . 116 4.14 Modified VIP Caching Structure . 122 4.15 VLAN Configurations of SANDIE Testbed . 125 A.1 Comparison of System 1 and System 2 in the Proof of Proposition 4 . 156 A.2 Comparison of the Proactive System and the Virtual System in the Proof of Proposi- tion 4.
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