A Mobile Data Management Architecture for Interoperability of Resource and Context Data
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A Mobile Data Management Architecture for Interoperability of Resource and Context Data Von der Fakultät für Informatik, Elektrotechnik und Informationstechnik der Universität Stuttgart zur Erlangung der Würde eines Doktors der Naturwissenschaften (Dr. rer. nat.) genehmigte Abhandlung Vorgelegt von Andreas Markus Brodt aus Gaildorf Hauptberichter: Prof. Dr.-Ing. habil. Bernhard Mitschang Mitberichter: Prof. Dr. Albrecht Schmidt Tag der mündlichen Prüfung: 11. April 2013 Institut für Parallele und Verteilte Systeme (IPVS) 2013 ACKNOWLEDGEMENTS First of all, I want to thank my doctoral advisor, Prof. Bernhard Mitschang, for giving me the opportunity to work on this challenging topic in his research group. I would also like to thank him for his guidance, his support, and many interesting discussions over all the years. Through his guidance I learned a lot about conducting scientific research and his ideas gave me new insights into my work. Furthermore, I want to thank my current or former colleagues at the Institute of Parallel and Distributed Systems (IPVS) at Universität Stuttgart, namely (in alphabet- ical order) Nazario Cipriani, Frank Dürr, Matthias Großmann, Carlos Lübbe, Daniela Nicklas, Florian Niedermann, Oliver Schiller, Holger Schwarz, and Christoph Stach. Thanks for the great time working together with you all! Special thanks goes to Sailesh Sathish from Nokia Research Center, who brought up brilliant ideas and with whom we published several papers. Also Kate Alhola, Pertti Huuskonen, Harri Kiviahde, Olli Pettay, Josh Soref, Aarne Taube, Esko Törmäkangas, Jari Tenhunen, and Seppo Yliklaavu from Nokia and Nokia Research Center deserve to be mentioned here for supporting my work on this thesis. Also I would like to acknowledge the great work of my students and student assistants (in alphabetical order, again): Björn Dick, Alexander Martin, Oleg Marin, Victor Miyai, Dominik Morar, Bruno Nunes, Bastian Reitschuster, Tim Waizenegger, Alexander Wobser, and Thomas Würfel. Their hard work was a great support! Last but definitely not least, I want to express my sincere thanks to my wife, my daughter, and my parents for their continuous support, encouragement and patience during my work on this thesis. Andreas Brodt Gerlingen, 19. April 2013 3 CONTENTS List of Acronyms9 Zusammenfassung 13 Abstract 17 1 Introduction 19 1.1 Motivation: Interoperability........................... 19 1.1.1 Interoperability at the Data Management Level.......... 21 1.1.2 Spatial Interoperability......................... 21 1.1.3 Interoperability between Devices................... 22 1.1.4 Interoperability with Web Applications............... 22 1.2 Requirements................................... 23 1.2.1 Data Model................................ 23 1.2.2 Integrated Data Management System................ 23 1.2.3 Ad-hoc Inter-Device Connectivity................... 24 1.2.4 Browser-based Data Access for Web Applications......... 24 1.3 Contributions and Outline of this Thesis................... 24 2 Mobile Data Management Architecture 27 2.1 State of the Art.................................. 27 2.1.1 Domain-specific APIs.......................... 28 2.1.2 Semantic Web and Semantic Desktop................ 28 2.1.3 Interoperability with Web Applications............... 29 2.1.4 Summary................................. 30 2.2 Platform Architecture............................... 30 2.3 The Data Management Layer.......................... 33 5 2.4 Data Model..................................... 34 2.5 Access Control................................... 35 2.6 Summary and Outlook.............................. 38 3 Efficient Attribute Retrieval in RDF Triple Stores 39 3.1 State of the Art and Foundations........................ 40 3.1.1 The W3C Resource Description Framework (RDF)........ 40 3.1.2 The W3C SPARQL Protocol and RDF Query Language (SPARQL) 42 3.1.3 RDF Data Management Systems: Triple Stores........... 42 3.1.4 Execution Plans for SPARQL Queries................. 44 3.2 Attribute Retrieval Approach.......................... 45 3.2.1 The Pivot Index Scan Operator.................... 46 3.2.2 Optional Attributes........................... 48 3.2.3 Multi-Attributes............................. 48 3.2.4 Multiply Selected Attributes...................... 49 3.2.5 Related Work............................... 50 3.3 Plan Generation.................................. 50 3.3.1 Generating Canonical Plans...................... 50 3.3.2 Generating Plans with Pivot Index Scans.............. 51 3.3.3 Cost Model................................ 53 3.3.4 Cardinality Estimation......................... 53 3.3.5 Selective Attributes........................... 57 3.4 Attribute Retrieval Index............................. 60 3.5 Evaluation..................................... 62 3.5.1 Implementation............................. 63 3.5.2 Test Setup................................. 64 3.5.3 Resources versus Attributes...................... 64 3.5.4 Multi-Attributes............................. 68 3.5.5 Selective Attributes........................... 70 3.6 Summary and Outlook.............................. 73 4 Deep Integration of Spatial Query Processing into RDF Triple Stores 75 4.1 State of the Art and Foundations........................ 76 4.1.1 RDF Data Management......................... 76 4.1.2 The SPARQL Query Language..................... 79 4.2 Modeling and Querying Spatial Literals in RDF............... 81 4.2.1 Spatial Literals in RDF......................... 81 4.2.2 SPARQL Filter Functions........................ 82 6 Contents 4.3 Implementation.................................. 83 4.3.1 Architecture and Processing Model.................. 84 4.3.2 Spatial Selection Operator....................... 85 4.3.3 Spatial Index............................... 86 4.3.4 Storing the Features........................... 88 4.4 Evaluation..................................... 88 4.4.1 Test Setup................................. 88 4.4.2 Spatial Selection vs. Spatial Index.................. 90 4.4.3 Dictionary Performance......................... 91 4.4.4 Different Selectivities.......................... 93 4.4.5 Multiple Spatial Features per Resource............... 96 4.5 Cardinality Estimation.............................. 96 4.5.1 Related Work............................... 98 4.5.2 Approach: Buckets and Frequent Path Bundles.......... 101 4.5.3 Evaluation................................. 108 4.6 Summary and Outlook.............................. 115 5 Ad-hoc Inter-Device Connectivity 117 5.1 Ad-hoc Smart Spaces............................... 118 5.1.1 Autonomous............................... 119 5.1.2 Highly Dynamic............................. 119 5.1.3 Complementary............................. 119 5.1.4 Practical and Consumer-oriented................... 119 5.2 Incentives for Ad-hoc Smart Spaces...................... 120 5.3 Technical Foundations and Architecture................... 121 5.3.1 Bluetooth Networking.......................... 122 5.3.2 Architecture of an Ad-hoc Smart Space Middleware....... 122 5.4 Resource Discovery in Bluetooth-based Ad-hoc Smart Spaces...... 123 5.4.1 Request Flooding............................. 125 5.4.2 Resource Flooding............................ 125 5.4.3 Publish/Subscribe............................ 125 5.4.4 Gnutella-Inspired............................. 126 5.4.5 Central Directory............................. 127 5.4.6 Random Replication........................... 127 5.4.7 Simulation Environment........................ 127 5.4.8 Evaluation................................. 130 5.5 Sample Ad-hoc Smart Space Applications.................. 136 5.5.1 Global Positioning System (GPS) Sharing Demo.......... 136 5.5.2 Spontaneous Team Meeting Solution (STEAMS)......... 138 Contents 7 5.6 Summary and Outlook.............................. 141 6 Interoperability with Web Applications 143 6.1 Foundations.................................... 144 6.1.1 Background: From Static Documents to Interactive Web Appli- cations................................... 144 6.1.2 Browser-local Storage.......................... 146 6.1.3 Context Provisioning for Web Applications............. 147 6.1.4 Summary................................. 149 6.2 Achieving Local Interoperability: The Repository Web-API........ 149 6.2.1 API Definition............................... 151 6.2.2 Access Control.............................. 151 6.2.3 Sample Web Applications........................ 154 6.3 Local and Remote Interoperability: Context-aware Mashups....... 156 6.3.1 The TELAR Mashup Platform...................... 158 6.3.2 NexusWeb................................. 162 6.4 Mobile Location-based Browser Games.................... 165 6.4.1 Examples for Mobile Location-based Browser Games....... 166 6.4.2 Properties of Mobile Location-based Browser Games....... 169 6.5 Summary and Outlook.............................. 172 7 Conclusions 175 Outlook.......................................... 178 List of Figures 179 List of Listings 181 Bibliography 183 Curriculum Vitae 195 8 Contents LISTOF ACRONYMS We use the following acronyms throughout this document: Ajax Asynchronous JavaScript and XML API Application Programming Interface ARM Advanced RISC Machines ASR Area Service Register AWM Augmented World Model AWML Augmented World Modeling Language AWQL Augmented World Query Language CAN Contend Addressable Network CPU Central Processing Unit CSS Cascading Style Sheets DBMS Data Base Management System DCCI Delivery Context: Client Interfaces DDR Double Data Rate DMS Data Management