Thinking Networks - The Large and Small of it: Autonomic and Reasoning Processes for Information Networks

It is clear today how much people are dependent on digital information sources, where networks are the prevalent organisational structure. As this dependency grows then so will the demand for a higher quality of information, where we are now moving into a service-based environment. This book describes different aspects of such an environment and is both important and timely for future Internet-based or mobile information networks. It considers specifically how intelligence can be added to these networks and what added benefits the intelligence might bring. For example, can a network intelligently optimise the services that it provides, or work out how to solve a more difficult task for a user? This book is mainly a research monograph, but it also contains blue sky research sections and also some informative or teaching sections. The book covers areas such as Artificial Intelligence (including Autonomous systems; Intelligent, Cognitive or Neural Network-like systems, and Bio-inspired networks), Internet/p2p/mobile networks, Knowledge management, SOA, Semantic Networks (Semantic Web, Ontologies, Web Services, Grid), XML-based languages and query processes. The second half of the book discusses some research ideas undertaken by the author. These are in the areas of self-organisation and reasoning, through the bio-inspired methods of stigmergy and reinforcement learning. The research proposes different levels of reasoning that can be performed over an information network and would be of interest to both academic or industrial researchers looking to build these intelligent systems. The suggested architecture however could be used to build networks that range in size from large-scale Internet-based networks to small local neural network-like structures, and ultimately offers an architecture on which to build a network that might even begin to 'think'.

Table of Contents:
Preface; Chapter 1. Introduction; 1.1 PEER-TO-PEER AND CLIENT-SERVER ARCHITECTURES; 1.2 BIO-INSPIRED NETWORKING; 1.2.1 Complex Adaptive Systems; 1.2.2 Evolutionary Computing; 1.3 PROPOSED SOLUTION; 1.4 SUMMARY; Chapter 2. Origins of Related Research; 2.1 INFORMATION NETWORKS; 2.2 ARTIFICIAL INTELLIGENCE; 2.3 SUMMARY; Chapter 3. Knowledge and Networks; 3.1 KNOWLEDGE REPRESENTATION; 3.1.1Logic or Rule-based Representations; 3.1.2 Compact Storage Structures; 3.2 KNOWLEDGE NETWORKS; 3.2.1 Hierarchical Structure; 3.3 SUMMARY; Chapter 4. Ontologies; 4.1 ONTOLOGY LANGUAGES; 4.2 AUTONOMIC ONTOLOGY CONSTRUCTION; 4.3 ONTOLOGIES FOR THE PERVASIVE COMPUTING ENVIRONMENT; 4.4 DATA INTEGRATION; 4.5 AUTOMATIC SERVICE CALLS THROUGH ONTOLOGY MAPPING; 4.6 FOLKSONOMIES; 4.7 COMMUNITIES OF PRACTICE; 4.8 SUMMARY AND CONCLUSIONS; Chapter 5. Query Languages; 5.1 AUTONOMOUS QUERY SYSTEMS; 5.2 DECLARATIVE XML-BASED QUERY LANGUAGES; 5.2.1 Declarative Optimisation; 5.3 DEDUCTIVE XML-BASED QUERY LANGUAGES; 5.4 DISTRIBUTED XML-BASED QUERY LANGUAGES; 5.5 REACTIVE XML-BASED QUERY LANGUAGES; 5.6 SUMMARY; Chapter 6. Services-Based Networks; 6.1 SERVICE-ORIENTED ARCHITECTURES; 6.2 WEB SERVICES AND THE GRID; 6.2.1 Web Services; 6.2.2 Grid Computing; 6.3 SUMMARY; Chapter 7. Autonomic Service-Based Networks; 7.1 AUTONOMIC COMPUTING; 7.1.1 Agent-Based Systems; 7.1.2 Autonomic Computing Principles; 7.1.3 The Autonomic Architecture; 7.1.4 Autonomic Behaviours and Interactions; 7.1.5 Communication Interfaces; 7.1.6 Resource Management; 7.2 SCRIPTING LANGUAGES; 7.3 AUTONOMIC SERVICE MANAGEMENT; 7.3.1 Deployment; 7.3.2 Discovery and Composition; 7.4 SUMMARY; Chapter 8. Dynamic Linking; 8.1 THE LINKING PROCESS; 8.2 THE LINKING STRUCTURE; 8.2.1 Query Caching; 8.2.2 Linking Methods; 8.3 RELATED WORK IN STIGMERGIC SELF-ORGANISATION; 8.4 DIRECT INFORMATION RETRIEVAL; 8.4.1 Test Objectives; 8.4.2 Test Environment; 8.4.3 Evaluation Statistics; 8.4.4 Performance Evaluations for Direct Information Retrieval; 8.4.5 Conclusions to the Tests; 8.5 AUTONOMIC SUPERVISION; 8.6 SUMMARY; Chapter 9. Intelligence from Experience; 9.1 AGGREGATED REASONING; 9.1.1 Reasoning Tests; 9.1.2 Related Work; 9.2 CENTRALISED AUTONOMIC REASONING; 9.2.1 Autonomic Linking; 9.2.2 Query Re-Writing to Include Rules; 9.2.3 Conclusions on the Centralised Approach; 9.3 A SYMBOLIC NEURAL NETWORK; 9.3.1 The Symbolic Approach to AI; 9.3.2 The Distributed Approach to AI; 9.3.3 Comparing the Classical AI Models with a Combined Model; 9.3.4 Autonomic Input Environment; 9.3.5 Existing Rule or Process Creation Techniques; 9.3.6 Higher-Level Concepts; 9.3.7 Integrating Rules; 9.3.8 Overall Cognitive Architecture; 9.3.9 Query Examples; 9.3.10 An Example Application for a Cognitive Brain; 9.4 SUMMARY; Chapter 10. Blurring the Human - Computer Interface; 10.1 SUMMARY; Chapter 11. The Open Source licas Distributed Communication Software; 11.1 NETWORK ARCHITECTURE; 11.2 METADATA USED BY THE SYSTEM; 11.3 THE COMMUNICATION PROTOCOL; 11.4 SUMMARY; Chapter 12. Discussion; 12.1 IMPLICATIONS OF THE WORK; 12.2 JOINING UP THE DOTS; 12.3 LOOKING INTO THE FUTURE; 12.3.1 Last Chance to Complain; 12.3.2 Social Interaction Aspects; References; Index

About the Author :
Kieran Greer is a researcher with over 10 years of experience working on projects at the two Universities in Northern Ireland. He specialises in R&D in the areas of Artificial Intelligence and Distributed Information Systems. This is his first book, which is related to his research at the University of Ulster. More recently, he has been developing his own innovative software products and developing the research ideas further. Details about this can be found on his distributedcomputingsystems.co.uk web site.