Xhafa / Barolli Complex Intelligent Systems and Their Applications

1. Auflage 2010
ISBN: 978-1-4419-1636-5
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 274 Seiten

'Complex Intelligent Systems and Applications' presents the most up-to-date advances in complex, software intensive and intelligent systems. Each self-contained chapter is the contribution of distinguished experts in areas of research relevant to the study of complex, intelligent, and software intensive systems. These contributions focus on the resolution of complex problems from areas of networking, optimization and artificial intelligence. The book is divided into three parts focusing on complex intelligent network systems, efficient resource management in complex systems, and artificial data mining systems. Through the presentation of these diverse areas of application, the volume provides insights into the multidisciplinary nature of complex problems. Throughout the entire book, special emphasis is placed on optimization and efficiency in resource management, network interaction, and intelligent system design. This book presents the most recent interdisciplinary results in this area of research and can serve as a valuable tool for researchers interested in defining and resolving the types of complex problems that arise in networking, optimization, and artificial intelligence.

Autoren/Hrsg.

Xhafa, Fatos

Barolli, Leonard

Inhaltsverzeichnis

1;Preface;6
1.1;Acknowledgements;8
2;Contents;9
3;List of Contributors;11
4;Efficient Integration of Complex Information Systems in the ATM Domain with Explicit Expert Knowledge Models;14
4.1;Introduction and Motivation;15
4.2;Objectives and Contribution;16
4.3;Related Work;18
4.3.1;Semantic Data Integration;18
4.3.2;Ontologies for Semantic Integration;20
4.4;Making Integration Knowledge Explicit;22
4.4.1;Abstract Integration Scenario Ontology;22
4.4.2;Domain-Specific Ontology;22
4.4.3;Integration System Ontology;23
4.5;SEEK-ATM Process Description;24
4.5.1;Traditional Integration Approach;24
4.5.2;SEEK-ATM Integration Approach;24
4.6;Added Value from Explicit Knowledge;26
4.6.1;Automated Identification of Integration Partner Candidates;26
4.6.2;Generation of Transformation Instructions;26
4.6.3;Generation of System Integration Configuration;27
4.7;Evaluation;27
4.7.1;Integration Effort;27
4.7.2;QA Efficiency;29
4.7.3;Model Complexity;29
4.7.4;Level of Automation Support;29
4.8;Conclusion and Future Work;30
4.9;References;31
5;An Ontology-Based Approach for Supporting Business-IT Alignment;33
5.1;Introduction;34
5.2;Background;34
5.2.1;What is Business-IT Alignment?;34
5.2.2;The B-SCP Framework;35
5.2.3;Seven-Eleven Japan Example;37
5.3;Related Work;38
5.4;Objectives and Contributions;43
5.4.1;Adding Semantics to the B-SCP Framework;43
5.4.2;Why an Ontology Based Approach?;44
5.4.3;Business Motivation Model Ontology;45
5.5;Discussion and Results;47
5.6;Future Work;51
5.7;Conclusion;51
5.8;References;52
6;EPCIS-Based Supply Chain Event Management;55
6.1;Introduction;56
6.2;EPCglobal Network;58
6.2.1;EPCglobal Architecture Framework;58
6.2.2;Electronic Product Code;60
6.2.3;EPC Information Services;60
6.3;Business Application;62
6.4;Decentralized EPCIS-Based SCEM;64
6.4.1;Data Layer;64
6.4.2;Protocol Layer;65
6.4.3;Application Layer;69
6.5;Quantitative Comparison of Two Architecture Approaches;70
6.5.1;EPCIS-Based Event Sharing Using Event Pull;70
6.5.2;EPCIS-Based SCEM Using Event Push (Our Proposal);72
6.5.3;Evaluation;72
6.5.3.1;Parameters;73
6.5.3.2;Efficient Use of Network Capacity;73
6.5.3.3;Efficient Use of Storage Capacity;74
6.5.3.4;Reliability;75
6.5.4;Results;76
6.6;Discussion;77
6.7;Conclusions and Future Work;78
6.8;References;79
7;Cost-Benefit Analysis to Hedge with Third-Party Producers in Demand-Driven Production;81
7.1;Introduction;81
7.2;Related Work;82
7.3;Cost-Benefit Analysis to Hedge with Third-Party Producers;86
7.4;Probabilistic Approach for Cost-Benefit Analysis to Hedge with Third-Party Producers;89
7.5;Conclusion;92
7.6;References;93
8;A Security Assurance Model to Holistically Assess the Information Security Posture;94
8.1;Why Is Information Security Assessment a Complex Task?;94
8.1.1;Traditional Assessment Procedures;95
8.1.2;New Challenges Regarding the Assessment of InfoSec;96
8.1.3;A New Multidimensional InfoSec Assessment Framework;97
8.2;Assurance Analysis for an Effective and Efficient InfoSec Assessment Framework;99
8.2.1;Security Assurance Principles;99
8.2.2;An Assurance Related Concept: The Trust;100
8.3;An Holistic InfoSec Assurance Assessment Model (ISAAM);102
8.3.1;The Structure;102
8.3.1.1;Lessons Learned from the Current Methodologies Related to the InfoSec Assurance Structure;102
8.3.1.2;The Holistic InfoSec Assurance Assessment Model (ISAAM) Structure;105
8.3.2;The Security Quality;107
8.3.2.1;State of the Art Related to the Quality Issues;107
8.3.2.2;Quality Aspects within the Holistic InfoSec Assurance Assessment Model (ISAAM);109
8.3.3;The Requirements Side (Maturity Levels);110
8.3.3.1;State of the Art Regarding the InfoSec Maturity Levels;110
8.3.3.2;The Holistic InfoSec Assurance Assessment Model (ISAAM) Maturity Level;112
8.3.3.2.1;Level 1: Fortuitous;112
8.3.3.2.2;Level 2: Structured;112
8.3.3.2.3;Level 3: Functional;113
8.3.3.2.4;Level 4: Analyzable;113
8.3.3.2.5;Level 5: Effective;113
8.3.4;Expected Outputs of the ISAA Evaluation Model;114
8.4;Conclusion;117
8.5;References;117
9;Risk-Aware Business Process Management-Establishing the Link Between Business and Security;120
9.1;Introduction;121
9.2;Related Work;122
9.3;Steps Required to Perform Risk-Aware Business Process Management;132
9.3.1;Perform Program Management;133
9.3.2;Determine As-Is Situation;133
9.3.3;Reengineer Processes;134
9.3.4;Implement Processes;135
9.3.5;Review and Evaluate;136
9.4;A Reference Model for Risk-Aware Business Process Management;136
9.5;Application Scenarios;139
9.6;Conclusion;143
9.7;References;145
10;Self-Optimised Tree Overlays Using Proximity-Driven Self-Organised Agents;147
10.1;Introduction;147
10.2;Objectives and Contributions;148
10.2.1;Applications;148
10.2.2;Problem Statement;149
10.2.2.1;Self-Organisation;149
10.2.2.2;Self-Optimisation;150
10.2.2.3;Application Independence;150
10.2.3;System Overview;151
10.3;Related Work;151
10.3.1;Literature Review;152
10.3.1.1;Application Domain;152
10.3.1.2;Optimisation Metrics;152
10.3.1.3;Complementary Overlays;153
10.3.1.4;Build and Maintenance;153
10.3.1.5;Decentralisation Level;154
10.3.1.6;Proactiveness vs. Reactiveness;154
10.3.2;Open Issues;154
10.4;Approach;155
10.5;Application Agent;156
10.5.1;Robustness (r);156
10.5.2;Node Degree (n);156
10.5.3;Expected Response Time (tr);156
10.5.4;Register;157
10.5.5;Build;157
10.5.6;Connect;157
10.5.7;Unregister;157
10.6;Self-Organisation Agent;157
10.6.1;Knowledge;157
10.6.1.1;Random View (R);158
10.6.1.2;Proximity View (M);158
10.6.1.3;Tree View (T);158
10.6.2;Components;159
10.6.2.1;Proximity Manager;159
10.6.2.2;Random Sampling;159
10.6.2.3;Proximity Sampling;159
10.6.2.4;Reconfiguration Manager;159
10.6.2.5;Tree Manager;161
10.6.2.6;Reaction Manager;162
10.6.3;Service Layer Architecture;162
10.6.3.1;PAROS;162
10.6.3.2;ARMOS;162
10.6.3.3;ATOM;162
10.7;System Control Agent;163
10.7.1;Bootstrapping;163
10.7.2;Termination;163
10.8;Evaluation of the Proposed Approach;164
10.8.1;Simulation Settings;164
10.8.2;Results;165
10.8.3;Discussion of Experimental Results;167
10.9;Conclusions and Future Work;169
10.10;References;169
11;Filtering Order Adaptation Based on Attractor Selection for Data Broadcasting System;172
11.1;Introduction;172
11.2;Information Filtering System;173
11.2.1;Mobile Environment;173
11.2.2;Filtering Architecture;174
11.2.3;Filtering Cost;175
11.3;Attractor Selection;176
11.3.1;Adaptive Response by Attractor Selection;176
11.3.2;Advantages of Attractor Selection;178
11.4;Proposed Methods;179
11.4.1;Attractor Selection (AS) Method;179
11.4.1.1;Calculation of the Filtering Cost;180
11.4.1.2;Calculation of the Activity;180
11.4.1.3;Calculation of the Selection Priority;180
11.4.1.4;Flow Chart;181
11.4.1.5;Problems of the AS Method;182
11.4.2;Extended Methods;182
11.4.2.1;AS-M Method;182
11.4.2.2;AS-P Method;183
11.4.2.3;AS-MP Method;183
11.5;Evaluation;183
11.5.1;Simulation Environment;184
11.5.2;Comparison Methods;185
11.5.3;Evaluation Criteria;186
11.5.4;Simulation Results;187
11.5.4.1;Impact of Calculation Cycle in the Cyclic Adaptation Method;187
11.5.4.2;Comparison among Methods;187
11.5.4.3;Impact of beta on the AS Method;191
11.5.4.4;Impact of gamma on the AS Method;191
11.5.4.5;Impact of delta on the AS Method;191
11.5.4.6;Impact of x on the AS Method;192
11.5.4.7;Impact of ci;192
11.5.4.8;Impact of the Number of Filters;194
11.6;Conclusions;194
11.7;References;195
12;StreamAPAS: Query Language and Data Model;196
12.1;Introduction;196
12.2;Data Stream Processing;197
12.3;Query Language;202
12.3.1;Structure of Query Language;202
12.3.2;Syntax of Unit and Task;204
12.3.3;Attribute Tree;205
12.3.4;Functions;207
12.4;Linear Road Benchmark;208
12.4.1;CQL;209
12.4.2;Example Queries in StreamAPAS;210
12.5;Further Work;211
12.6;Related Work;212
12.7;Conclusion;213
12.8;References;213
13;Agent-Supported Programming of Multicore Computing Systems;215
13.1;Introduction;216
13.2;Recent Developments in Parallel Computing Systems;217
13.2.1;Parallel and Distributed Programming;217
13.2.2;Compilation Techniques;219
13.2.3;Multi-Core Architectures;220
13.3;Intelligent Programming of Multi-Core Systems;222
13.3.1;Methodology;222
13.3.1.1;Model-Driven Development (MDD);222
13.3.1.2;Parallel Building Blocks;223
13.3.1.3;Intelligent Software Agents;223
13.3.2;Programming Environment;224
13.3.2.1;High-level Program Composition;224
13.3.2.2;Design Space Exploration;225
13.3.2.3;Resource Usage Optimization;225
13.4;Example;226
13.5;Related Work;228
13.6;Conclusions;229
13.7;References;230
14;Multimodal and Agent-Based Human-Computer Interaction in Cultural Heritage Applications: an Overview;233
14.1;Introduction;233
14.2;Multimodal Human-Computer Interaction in Cultural Heritage Applications;234
14.3;A Timeline of Cultural Heritage Fruition Applications;235
14.4;Multimodal Mobile Access to Services and Contents in Cultural Heritage Sites;237
14.5;Agent-Based Human-Computer Interaction in Cultural Heritage Applications;242
14.5.1;Multi-Agent System-Based Solutions for AB-HCI;245
14.5.2;Conversational Agent Based Solutions for AB-HCI;247
14.5.3;Discussions and Comparisons;248
14.6;Conclusions;250
14.7;References;251
15;Reinforced Operators in Fuzzy Clustering Systems;254
15.1;Introduction;254
15.2;Fusion Operators;255
15.3;Fusion Operators in Fuzzy Sets and Possibility Theory;256
15.4;The Triple Pi Operator;258
15.5;The Mean Triple Pi;259
15.5.1;The Mean Triple Pi;259
15.5.2;The Mean Reinforcement;261
15.6;LAMDA Clustering System;263
15.7;Experimental Results;266
15.8;Uncertainties and Maximum of Modulus of Wavelet Transform;267
15.9;Classification and Maximum of Modulus of Wavelet Transform;268
15.9.1;The Continuous Wavelet Transform;268
15.9.2;Maximum into the Classification;271
15.10;Conclusion;272
15.11;References;272
16;Index;274