ONTOLOGY DRIVEN MULTI-AGENT SYSTEMS: AN ARCHITECTURE FOR .
ONTOLOGY DRIVEN MULTI-AGENT SYSTEMS: ANARCHITECTURE FOR SENSOR WEB APPLICATIONSbyDESHENDRAN MOODLEYSubmitted in fulfillment of the academic requirements for the degree of Doctor of Philosophy in theSchool of Computer Science, Faculty of Science and Agriculture, University of KwaZulu-Natal,Durban, South Africa, December 2009As the candidate’s supervisor I have approved this dissertation for submission.Signed:Name:Date:
ABSTRACTAdvances in sensor technology and space science have resulted in the availability of vast quantities ofhigh quality earth observation data. This data can be used for monitoring the earth and to enhance ourunderstanding of natural processes. Sensor Web researchers are working on constructing a worldwidecomputing infrastructure that enables dynamic sharing and analysis of complex heterogeneous earth observation data sets. Key challenges that are currently being investigated include data integration; servicediscovery, reuse and composition; semantic interoperability; and system dynamism. Two emerging technologies that have shown promise in dealing with these challenges are ontologies and software agents.This research investigates how these technologies can be integrated into an Ontology Driven Multi-AgentSystem (ODMAS) for the Sensor Web.The research proposes an ODMAS framework and an implemented middleware platform, i.e. theSensor Web Agent Platform (SWAP). SWAP deals with ontology construction, ontology use, and agentbased design, implementation and deployment. It provides a semantic infrastructure, an abstract architecture, an internal agent architecture and a Multi-Agent System (MAS) middleware platform. Distinguishing features include: the incorporation of Bayesian Networks to represent and reason about uncertainknowledge; ontologies to describe system entities such as agent services, interaction protocols and agentworkflows; and a flexible adapter based MAS platform that facilitates agent development, execution anddeployment. SWAP aims to guide and ease the design, development and deployment of dynamic alertingand monitoring applications. The efficacy of SWAP is demonstrated by two satellite image processingapplications, viz. wildfire detection and monitoring informal settlement. This approach can provide significant benefits to a wide range of Sensor Web users. These include: developers for deploying agentsand agent based applications; end users for accessing, managing and visualising information provided byreal time monitoring applications, and scientists who can use the Sensor Web as a scientific computingplatform to facilitate knowledge sharing and discovery.An Ontology Driven Multi-Agent Sensor Web has the potential to forever change the way in whichgeospatial data and knowledge is accessed and used. This research describes this far reaching vision,identifies key challenges and provides a first step towards the vision.ii
PREFACEThe research work described in this dissertation was carried out in the School of Computer Science,University of KwaZulu-Natal, Durban, from March 2001 to December 2009, under the supervision ofProf. Jules R. Tapamo and Prof. Johnson D.M. KinyuaThese studies represent original work by the author and have not otherwise been submitted in any formfor any degree or diploma to any tertiary institution. Where use has been made of the work of others it isduly acknowledged in the text.iii
DECLARATION 1 - PLAGIARISMI, Deshendran Moodley, declare that:1. The research reported in this thesis, except where otherwise indicated, is my original research.2. This thesis has not been submitted for any degree or examination at any other university.3. This thesis does not contain other persons’ data, pictures, graphs or other information, unlessspecifically acknowledged as being sourced from other persons.4. This thesis does not contain other persons’ writing, unless specifically acknowledged as beingsourced from other researchers. Where other written sources have been quoted, then:(a) Their words have been re-written but the general information attributed to them has beenreferenced(b) Where their exact words have been used, then their writing has been placed in italics andinside quotation marks, and referenced.5. This thesis does not contain text, graphics or tables copied and pasted from the Internet, unlessspecifically acknowledged, and the source being detailed in the thesis and in the References sections.Signed:iv
DECLARATION 2 - PUBLICATIONS1. M OODLEY, D., AND K INYUA , J. A multi-agent system for electronic job markets. In Proc.6th International conference on Business Information Systems, Colorado Springs, USA, 4-6 June2003, published by Dept. of Management Info. Systems, The Poznan University of Economics,Poznan (2003), pp. 42–482. M OODLEY, D. The future of the Internet: The semantic web, web services and a multi-agentsystem infrastructure for the Internet. In Proc. South African Computer Lecturers Association2004, 4-6 July Durban, 2004 (2004)3. M OODLEY, D., AND K INYUA , J. D. M. Towards a multi-agent infrastructure for distributed Internet applications. In 8th Annual Conference on WWW Applications, Bloemfontein, South Africa,5-6 September (2006)4. M OODLEY, D., T ERHORST, A., S IMONIS , I., M C F ERREN , G., AND VAN DEN B ERGH , F. Usingthe sensor web to detect and monitor the spread of wild fires. In Second International Symposiumon Geo-information for Disaster Management (Gi4DM) September 25-26, Pre-Conference Symposium to ISPRS TC-IV and ISRS Symposium on Geospatial Databases for Sustainable DevelopmentSeptember 27-30, at Goa, India (2006)5. M OODLEY, D., AND S IMONIS , I. A new architecture for the sensor web: the SWAP-framework.In Semantic Sensor Networks Workshop, A workshop of the 5th International Semantic Web Conference ISWC 2006, November 5-9, Athens, Georgia, USA (2006)6. T ERHORST, A., S IMONIS , I., AND M OODLEY, D. A service-oriented multi-agent systems architecture for the sensor web. In SAEON Summit, Centurion, South Africa (2006)7. M OODLEY, D., VAHED , A., S IMONIS , I., M C F ERREN , G., AND Z YL , T. V. Enabling a newera of earth observation research: scientific workflows for the sensor web. Ecological Circuits 1(2008), 20–238. T ERHORST, A., M OODLEY, D., S IMONIS , I., F ROST, P., M C F ERREN , G., ROOS , S., ANDVAN DEN B ERGH , F. Geosensor Networks, Lecture Notes in Computer Science, Volume 4540/2008.Springer-Verlag, 2008, ch. Using the Sensor Web to Detect and Monitor the Spread of VegetationFires in Southern Africa, pp. 239–251Signed:v
ACKNOWLEDGEMENTSMany people have supported me through this endeavour. I am deeply grateful to my wife for her patience,understanding, support and for allowing the PhD to permeate our lives over the past few years.I wish to express sincere gratitude to my supervisor Jules Tapamo for his support and guidance, andto my co-supervisor Johnson Kinyua for his support and guidance through the early stages.I would like to thank my parents, my family and my dear friends who have supported me. A specialthank you to Anban Pillay for being a dear friend, and for willing to sacrifice many hours for proofreading.I wish to also acknowledge and thank: Chetna Parbhoo for designing and implementing the secondcase study application as part of her Masters research; Pravi Moodley who assisted with the proof reading; members of the ICT4EO and KSG groups at the Meraka Institute, CSIR, Pretoria, specifically IngoSimonis and Tommie Meyer.I also acknowledge the financial support provided by the National Research Foundation and theGerman Academic Exchange Service (DAAD) .vi
TABLE OF CONTENTSPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iiiDeclarations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ivAcknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .viTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .viiList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xiiList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviiiList of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xixChapter 1Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11.1Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11.2Problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31.3Expected impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31.4The SWAP framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41.4.1Semantic infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41.4.2MASII: An Internet Wide Multi Agent System middleware . . . . . . . . . . . .51.4.3Framework for designing and developing Sensor Web agents and applications . .51.4.4Application case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6Organisation of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61.5Chapter 22.1Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8The Sensor Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82.1.1Our vision of the Sensor Web . . . . . . . . . . . . . . . . . . . . . . . . . . .102.1.2OGC Sensor Web Enablement . . . . . . . . . . . . . . . . . . . . . . . . . . .122.1.3GeoSwift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13vii
2.22.32.42.5Software agents and multiagent systems for Internet Computing . . . . . . . . . . . . .142.2.1Agent operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152.2.2MAS infrastructure models and platforms . . . . . . . . . . . . . . . . . . . . .182.2.3Challenges for building an Internet Wide MAS (IWMAS) . . . . . . . . . . . .20Ontologies and the Semantic Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . .222.3.1Ontology Representation languages . . . . . . . . . . . . . . . . . . . . . . . .252.3.2Ontology development and management . . . . . . . . . . . . . . . . . . . . . .292.3.3Ontology based systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .322.3.4Agents and the Semantic Web . . . . . . . . . . . . . . . . . . . . . . . . . . .33Agents and ontologies on the Sensor Web . . . . . . . . . . . . . . . . . . . . . . . . .342.4.1Agent based approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .342.4.2Ontology based Sensor Web approaches . . . . . . . . . . . . . . . . . . . . . .36Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39Chapter 3Design of an Internet Wide Multi-Agent System Infrastructure . . . . . . . .403.1Requirements for a single global multi-agent infrastructure . . . . . . . . . . . . . . . .403.2The Multi-Agent Infrastructure for the Internet . . . . . . . . . . . . . . . . . . . . . .423.2.1An abstract architecture for a IWMAS . . . . . . . . . . . . . . . . . . . . . . .42MASII design and operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .453.3.1Registry Agent (RA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .463.3.2Adapter agent (AA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .463.3.3Platform implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .473.3.4Application development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .483.4Application deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .493.5Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .493.3Chapter 4Design of the Sensor Web Agent Platform . . . . . . . . . . . . . . . . . . . .514.1Our vision of the Sensor Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .514.2The SWAP Abstract Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .524.2.1Sensor Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .524.2.2Knowledge Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54viii
4.34.44.54.64.74.84.2.3Application Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .544.2.4Incorporating OGC services . . . . . . . . . . . . . . . . . . . . . . . . . . . .55Overview of the SWAP Ontological Infrastructure . . . . . . . . . . . . . . . . . . . . .554.3.1Rationale behind the SWAP ontology . . . . . . . . . . . . . . . . . . . . . . .554.3.2Swap rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57The SWAP conceptual ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . .594.4.1Thematic representation and reasoning . . . . . . . . . . . . . . . . . . . . . .604.4.2Spatial representation and reasoning . . . . . . . . . . . . . . . . . . . . . . . .624.4.3Temporal representation and reasoning . . . . . . . . . . . . . . . . . . . . . .644.4.4Uncertainty representation and reasoning . . . . . . . . . . . . . . . . . . . . .67The SWAP technical ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .674.5.1Representing data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .674.5.2Representing agents, services and interactions . . . . . . . . . . . . . . . . . . .684.5.3Representing workflows using OWL-S . . . . . . . . . . . . . . . . . . . . . .704.5.4Incorporating agent services into OWL-S . . . . . . . . . . . . . . . . . . . . .73Agent Discovery and Invocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .754.6.1The SWAP Directory Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . .754.6.2Service Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77SWAP Internal Agent Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . .784.7.1Internal Agent Architecture Overview . . . . . . . . . . . . . . . . . . . . . . .784.7.2Incorporating GIS development libraries . . . . . . . . . . . . . . . . . . . . . .784.7.3Mapping between ontology data instances and OpenGIS data objects . . . . . .80Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81Chapter 55.15.2Incorporating uncertainty into SWAP . . . . . . . . . . . . . . . . . . . . . .83Bayesian Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .845.1.1Bayesian Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84Bayesian Networks for the Sensor Web . . . . . . . . . . . . . . . . . . . . . . . . . .865.2.1An ontology for Bayesian Networks . . . . . . . . . . . . . . . . . . . . . . . .875.2.2Specifying Bayesian Networks . . . . . . . . . . . . . . . . . . . . . . . . . . .895.2.3The uncertainty reasoner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .99ix
5.3Discussion and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102Chapter 66.16.2Implementing SWAP applications . . . . . . . . . . . . . . . . . . . . . . . . 105Case study 1: wildfire detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056.1.1Application overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056.1.2Representing and reasoning about uncertainty for wildfire detection . . . . . . . 108SWAP Agent Operation and Implementation . . . . . . . . . . . . . . . . . . . . . . . . 1156.2.1Sensor Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156.2.2The MSG Sensor Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1196.2.3Tool Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1256.2.4The Contextual Algorithm (CA) Tool Agent . . . . . . . . . . . . . . . . . . . . 1306.2.5Workflow Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1356.2.6The Hotspot Detection Workflow Agent . . . . . . . . . . . . . . . . . . . . . . 1386.2.7Modeling Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1416.2.8The FireSpreadModeler Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . 1476.2.9Application Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1516.2.10 The Wildfire Detection Application Agent . . . . . . . . . . . . . . . . . . . . . 1556.2.11 User Agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1576.2.12 The Wildfire Detection User Agent . . . . . . . . . . . . . . . . . . . . . . . . 1606.3Deploying the Wildfire Detection Application . . . . . . . . . . . . . . . . . . . . . . . 1616.4Case study 2: monitoring informal settlements . . . . . . . . . . . . . . . . . . . . . . . 1636.56.4.1Application overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1646.4.2Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1656.4.3Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1676.4.4Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175Chapter 77.1Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176Context of this research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1767.1.1Software agents and multiagent systems . . . . . . . . . . . . . . . . . . . . . . 1767.1.2Ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177x
7.27.37.47.5Summary of results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1787.2.1Semantic framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1807.2.2Framework for designing, deploying and accessing agents and applications . . . 1847.2.3Usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187Comparison with other systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1897.3.1Agent based Sensor Web approaches . . . . . . . . . . . . . . . . . . . . . . . . 1897.3.2Non-agent based approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1907.3.3Other related work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192Limitations and future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1937.4.1Creating additional SWAP applications . . . . . . . . . . . . . . . . . . . . . . 1947.4.2Extending uncertainty and supporting quality of service . . . . . . . . . . . . . 1947.4.3Agent mobility and security . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1957.4.4Automation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1957.4.5Tool support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195Impact of research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196Appendix AThe SWAP ontologies and rules . . . . . . . . . . . . . . . . . . . . . . . . . . 198A.1 The swap-theme ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198A.2 The spatial ontology and rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199A.2.1 The swap-space ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199A.2.2 Spatial rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201A.3 The temporal ontology and rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202A.3.1 The swap-time ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202A.3.2 Temporal rules . . . . . . . . . . . . . . . . . . . . . . . . .
This research investigates how these technologies can be integrated into an Ontology Driven Multi-Agent System (ODMAS) for the Sensor Web. The research proposes an ODMAS framework and an implemented middleware platform, i.e. the Sensor Web Agent Platform (SWAP). SWAP deals with ontology construction, ontology use, and agent
community-driven ontology matching and an overview of the M-Gov framework. 2.1 Collaborative ontology engineering . Ontology engineering refers to the study of the activities related to the ontology de-velopment, the ontology life cycle, and tools and technologies for building the ontol-ogies [6]. In the situation of a collaborative ontology .
entities, classes, properties and functions related to a certain view of the world. The use of an ontology, translated into an active information system component, leads to Ontology-Driven Information Systems and, in the specific case of GIS, leads to what we call Ontology-Driven Geographic Information Systems.
method in map-reduce framework based on the struc-ture of ontologies and alignment of entities between ontologies. Definition 1 (Ontology Graph): An ontology graph is a directed, cyclic graph G V;E , where V include all the entities of an ontology and E is a set of all properties between entities. Definition 2 (Ontology Vocabulary): The .
Ontology driven clinical decision support frameworks An ontology is an explicit specification of a conceptualization. The term is borrowed from philosophy, where an ontology is a systematic account of existence. For AI systems, what “exists” is that which can be represented. When the knowledge of a domain is rep-
To enable reuse of domain knowledge . Ontologies Databases Declare structure Knowledge bases Software agents Problem-solving methods Domain-independent applications Provide domain description. Outline What is an ontology? Why develop an ontology? Step-By-Step: Developing an ontology Underwater ? What to look out for. What Is "Ontology .
Ontology provides a sharable structure and semantics in knowledge management, e-commerce, decision-support and agent communication [6]. In this paper, we described the conceptual framework for an ontology-driven semantic web examination system. Succinctly, the paper described an ontology required for developing
A Framework for Ontology-Driven Similarity Measuring Using Vector Learning Tricks Mengxiang Chen, Beixiong Liu, Desheng Zeng and Wei Gao, Abstract—Ontology learning problem has raised much atten-tion in semantic structure expression and information retrieval. As a powerful tool, ontology is evenly employed in various
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