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Special Graduate Schools
Graduate School of Information and Communication Technology
Department of Information and Communication
3. Theses(Master)
Self Healing 에서Casual Reasoning을 통한 Fault 자동 검출
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chaudhry, Junaid Ahsenali | - |
| dc.date.accessioned | 2019-10-21T07:13:35Z | - |
| dc.date.available | 2019-10-21T07:13:35Z | - |
| dc.date.issued | 2009-02 | - |
| dc.identifier.other | 9422 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/17458 | - |
| dc.description | 학위논문(박사)--아주대학교 정보통신전문대학원 :정보통신공학과,2009. 2 | - |
| dc.description.tableofcontents | ABSTRACT 5 ACKNOWLEDGEMENTS 6 INTRODUCTION 14 1.1 MOTIVATION 14 1.2 SCENARIO 15 1.3 ECONOMIC CONSIDERATIONS 16 1.4 PROBLEM STATEMENT 18 1.5 FOCUS 18 1.6 REQUIREMENTS 20 1.6.1Self Healing 21 1.6.2 Casual Reasoning 23 1.7 CHALLENGES 28 1.7.1 Challenge #1: Dynamism and Context-Awareness 28 1.7.2 Challenge #2: Portability 29 1.7.3 Challenge #3: Magnitude of Scale 29 1.7.4 Challenge #4: Heterogeneity 29 1.7.5 Challenge #4: Scale of Uncertainty 30 1.8 THESIS 30 1.9 CONTRIBUTION 30 1.10 CASE STUDY 30 1.11 WHAT THIS THESIS IS NOT 31 1.12 STRUCTURE OF THE DISSERTATION 2 CASE STUDY: AUTONOMIC HEALING-BASED SELF MANAGEMENT ENGINE 33 2.1 OVERVIEW 33 2.2 UBIQUITOUS NETWORKS INDUSTRY 33 2.3 AUTONOMIC HEALING-BASED SELF-MANAGEMENT ENGINE (AHSEN) 36 2.3.1 Software Architecture 36 2.4 AHSEN COMPONENTS 39 2.4.1 Normal Functionality Model (NFM) 39 2.4.2 Self Management Framework (SMF) 40 2.4.3 Service Lifecycle 42 2.5 APPLICATION SCENARIO 44 3 THE PROPOSED ARCHITECTURE 58 3.1 INTRODUCTION 58 3.2 PROCESS CONVERSION TO XML DOCUMENTS 58 3.3 ABNORMALITIES DETECTION 61 3.3.1 Tag Heterogeneity 62 3.3.2 Structural Heterogeneity 62 3.3.3 Assumptions 64 3.4 SIMILARITY MATRICES 66 3.4.1 Label Similarity 66 3.4.2 Pattern Similarity 72 3.4.3 Vertices Similarity 74 3.4.4 Tree Edit Distance Similarity 76 4 POLICY ENGINE 78 4.1 INTRODUCTION 78 4.2 SOFTWARE ARCHITECTURE81 4.2.1 Dynamically Adjustable Policy Engine 81 4.2.2 A Sample Scenario of the Dynamically Adjustable Rules 81 4.2.3 Code Generation and Operation in the Policy Engine 86 4.2.4 Software Architecture of the Policy Engine 87 4.2.5 Performance of the Policy Engine90 4.2.6 Experimental Environment 90 4.2.7 Performance Comparison 91 4.3 NOVEL RULE METHODOLOGY 94 5 RELATED WORK 98 5.1 OVERVIEW 98 5.2 AUTONOMIC NETWORK MANAGEMENT SYSTEMS 98 5.2.1 HYWINMARC 98 5.2.2 AMUSE 99 5.2.3 RoSES 99 5.2.4 AMUN 100 5.2.5 SMHMS 100 5.3 CASE-BASED REASONING SYSTEMS 101 5.3.1 CHEMREG 101 5.3.2 JColibri 101 5.3.3 IBROW Project 102 5.3.4 CBR*Tools 102 5.3.5 NaCoDAW 102 5.4 POLICY ENGINE 103 5.4.1 RETE 103 5.4.2 Business Rule Markup Language (BRML) 103 5.4.3 JSR-094 (Java Specification Request) 104 5.5 SIMILARITY APPROACHES 104 5.5.1 ELIXIR 104 5.5.2 XIRQL and XXL 104 5.5.3 Fuzzy weights 105 5.5.4 Relaxed weights 105 5.5.5 ApproXQL 105 5.5.6 Query Decomposition Approach 106 5.6 FAULT DETECTION 106 5.6.1 Expert Systems in Fault Detection 106 5.6.2 Neural Networks in Fault Detection 107 5.6.3 Qualitative simulation in on-line Fault Detection 107 5.6.4 On-line Expert systems in Fault Detection 107 6 IMPLEMENTATION 110 6.1 OVERVIEW 110 6.2 IMPLEMENTATION DETAILS 110 6.2.1 Similarity-based inverted index and pattern index 110 6.2.2 Create List of Fragments and Regions 113 7 PROTOTYPE 117 7.1 PARSING OF XML FILES 117 7.2 DOM OBJECT FOR EACH FILE CREATED 117 7.3 CONSTRUCT TREE TARGET 117 7.4 CONSTRUCT INVERTED INDEX 117 7.5 QUERY PROCESSING 119 7.6 CONSTRUCT PATTERN INDEX 119 7.7 FRAGMENTS CONSTRUCTION FORM PATTERN INDEX 119 7.8 DEMO SCREENSHOTS 123 8 EVALUATION 130 8.1 PERFORMANCE GRAPHS 130 8.1.1 Fault Detection and Traversal 130 8.1.2 Resource Utilization 133 8.1.3 Trends of Casual Reasoning based Fault Detection 135 9 CONTRIBUTIONS 138 9.1 CONTRIBUTIONS 138 9.2 CONCEPTUAL CONTRIBUTIONS 138 9.2.1 Casual Reasoning-based Fault Identification 138 9.2.2 Self Management Functional Hierarchy 138 9.2.3 Multifaceted Policy Engine Methodology 140 9.2.4 Healing Policy Generation 141 9.3 ARCHITECTURES 141 9.3.1 AHSEN 141 9.3.2 Policy Engine 142 9.4 SOFTWARE PROTOTYPES 143 10 CONCLUSION AND FUTURE WORK 145 10.1 FUTURE WORK 147 BIBLIOGRAPHY 149 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | Self Healing 에서Casual Reasoning을 통한 Fault 자동 검출 | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 정보통신전문대학원 | - |
| dc.contributor.department | 정보통신전문대학원 정보통신공학과 | - |
| dc.date.awarded | 2009. 2 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 567548 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000009422 | - |
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