Note: Intro -- Preface -- Acknowledgments -- Contents -- Contributors -- 1 Internet of Intelligent Things: Bringing Artificial Intelligence into Things and Communication Networks -- Abstract -- 1…Introduction -- 1.1 Internet of Things Challenges -- 2…Artificial Intelligence for Intelligent Sensing -- 3…Social Networks and the Internet of Intelligent Things -- 4…Pervasive Intelligent Robots -- 4.1 IoT and Urban Technologies -- 4.2 IoT Platforms for Home Automation/Ambient Intelligence -- 4.3 Smart Devices -- 5…Intelligent Large Scale Sensing -- 5.1 People-Centric Sensing -- 5.2 Ubiquitous Sensing -- 5.3 Location-Aware Sensing -- 5.4 OpportunisticOpportunistic Sensing and Participatory Sensing -- 5.5 Contextual Sensing -- 5.6 Machine Learning for Large-Scale Sensing -- 5.7 Sensing Architectures -- 6…The Cloud and the Internet of Intelligent Things -- 6.1 Wireless Sensor Networks Backend Infrastructures -- 6.2 Wireless Sensor Networks and Health Care -- 6.3 Machine-to-Machine (M2M) CommunicationsMachine-to-Machine Communications in the Cloud -- 6.4 Cloud Robotics -- 7…Conclusions -- References -- 2 Cloud Computing: Paradigms and Technologies -- Abstract -- 1…Introduction -- 2…Anatomy of Cloud Computing -- 2.1 Definition -- 2.2 Characteristics -- 2.3 Affects -- 2.4 Architecture -- 2.5 Technologies behind Cloud Computing -- 2.6 Advantages of the Use of Cloud Technology -- 3…Classifying Clouds and Vendors -- 3.1 Deployment Models -- 3.2 Service Models -- 3.2.1 Infrastructure-as-a-Service -- 3.2.2 Platform-as-a-Service -- 3.2.3 Software-as-a-Service -- 3.2.4 Data-as-a-Service -- 3.3 Cloud Vendors -- 4…Cloud Computing Aspects -- 4.1 Cost and Pricing -- 4.2 Service Level Agreement -- 4.3 Security -- 5…Cloud Computing and Distributed Computing Paradigms -- 5.1 Utility Computing Utility Computing Versus Cloud Computing. , 5.2 Volunteer Computing Volunteer Computing Versus Cloud Computing -- 5.3 Grid Computing Grid Computing Versus Cloud Computing -- 6…The Road Ahead -- 6.1 Lessons Learned in Cloud Adoption -- 6.2 Challenges and Future Research Directions -- 7…Conclusion -- References -- 3 A Comparison of Two Different Approaches to Cloud Monitoring -- Abstract -- 1…Introduction -- 2…Monitoring IaaS Cloud!IaaS Clouds -- 3…Related Work -- 4…Cloud Experience in European Research Projects -- 4.1 VISION VISIONCloud -- 4.2 mOSAIC -- 5…Monitoring in the VISION VISIONCloud platform -- 5.1 Overall Architecture and Requirements -- 5.2 Monitoring Architecture -- 5.3 Implementation Details -- 5.4 Event and Rulemonitoring!rules Format -- 6…Cloud AgencyCloud Agency -- 6.1 Monitoring Architecture -- 6.2 MeteringCloud Agency!metering the Cloud -- 6.3 Monitoring the Cloud -- 6.4 Implementation Details -- 7…Critical Analysis -- 8…Conclusion -- Acknowledgments -- References -- 4 Intuitive User Interfaces to Help Boost Adoption of Internet-of-Things and Internet-of-Content Services for All Disaster Management -- Abstract -- 1…Introduction -- 2…The Technology Supply Quest -- 3…Accessibility Matters: Opening Service Access to All -- 4…Setting up a Solution -- 4.1 The IOTC4ALL Service Model -- 4.2 Enhancing Services Components to Enrich Their Accessibility -- 4.3 The IOTC4ALL Marketplace -- 4.4 Smart Devices UI -- 4.4.1 Intelligent and Adaptive HCI -- 4.4.2 Ubiquitous Computing and Ambient Intelligence -- 4.4.3 From Unimodal to Multimodal Interfaces -- 4.4.4 Smart Devices Today -- 5…Conclusions and Future Work -- References -- 5 Intelligent Context: The Realization of Decision Support Under Uncertainty -- Abstract -- 1…Introduction -- 2…The Complexity of Context -- 3…Intelligent Context ProcessingContext!Intelligent context processing -- 3.1 The Context-Processing Algorithm. , 3.2 The Extended Context Processing AlgorithmContext!Extended context processing algorithm -- 3.2.1 Implementation -- 4…The Distribution Function -- 4.1 The Design of the Distribution Function -- 4.2 The Decision Boundary Proximity Issue -- 4.3 Partitioning and the Euclidean Distance Adjustment Analysis -- 4.3.1 An Analysis -- 4.4 Analysis Conclusions and Observations -- 5…Context Processing under UncertaintyContext!Uncertainty -- 6…Results and Discussion -- 6.1 Situational AwarenessContext!Situational awareness -- 7…Concluding Observations -- References -- 6 Autonomous Evolution of Access to Information in Institutional Decision-Support Systems Using Agent and Semantic Web Technologies -- Abstract -- 1…Introduction -- 2…Agent-Oriented Semantic Access -- 2.1 The generic system -- 2.2 The Legacy RDB System -- 2.3 The Semantic Query Access System -- 2.4 Decomposition of SQAS Use Cases -- 3…The SQAS Architecture -- 3.1 The High-Level Architecture of SQAS -- 3.2 The Roles of User Interface Agent -- 3.3 The Roles of Database Interface Agent -- 4…Agent-Oriented Middleware for Server Subsystems -- 4.1 The Database Interface Environment -- 4.2 A Note on Implementation Strategy -- 4.3 A Scenario for Agent-Assisted Ontology Development -- 5…Agent-Oriented Middleware for Client Subsystems -- 5.1 The User Interface Environment -- 5.2 A Scenario for Agent-Assisted Semantic Access -- 6…Closing Remarks -- 7…Conclusions -- References -- 7 A Research Survey on Large XML Data: Streaming, Selectivity Estimation and Parallelism -- Abstract -- 1…Introduction -- 1.1 Preliminaries -- 2…Selectivity Estimation -- 2.1 Properties of Selectivity Estimation Techniques -- 2.2 Path/Twig Selectivity Estimation Techniques -- 2.2.1 Synopsis-Based Estimation Techniques -- 2.2.2 Histogram-Based Estimation Techniques -- 3…Stream-Processing Approaches -- 3.1 Stream-Filtering Algorithms. , 3.2 Stream-Querying Algorithms -- 4…Parallel Query Processing -- 4.1 General Research on Decidability and Complexity -- 4.2 Data Distribution -- 4.3 Distribution and Parallel XPath Query Processing -- 4.4 Low-Level Implementation Techniques -- 4.5 DBMS and Join-Based Implementations -- 4.6 Map-Reduce, Hadoop Implementations -- 5…Conclusion -- References -- 8 Techniques and Applications to Analyze Mobility Data -- Abstract -- 1…Introduction -- 2…Collectingtrace collection Inter-cooperative Mobilitymobility Data -- 2.1 The HaggleHaggle Project -- 2.2 CRAWDADCRAWDAD -- 2.3 Socialsocial Tracer and HYCCUPS -- 2.3.1 Socialsocial Tracer -- 2.3.2 HYCCUPS -- 2.4 Benefits and Limitations -- 3…Techniques for Data Analysisdata analysis -- 3.1 Contact Timescontact time Distribution and Time of Day Dependence -- 3.2 Contact Predictabilitypredictability -- 3.3 Predictabilitypredictability of Interacting with Wirelesswireless Access Pointsaccess point -- 4…Experimental Results -- 4.1 Contact Timescontact time Distribution and Time of Day Dependence -- 4.1.1 UPB 2011 -- 4.1.2 UPB 2012 -- 4.2 Contact Predictabilitypredictability -- 4.3 Predictabilitypredictability of Interacting with Wireless Access Pointsaccess point -- 4.3.1 Rice -- 4.3.2 Nodobo -- 5…Conclusions and Future Work -- References -- 9 Memory Support Through Pervasive and Mobile Systems -- Abstract -- 1…Introduction -- 1.1 Evolution of Memory Prosthetics Devices -- 2…Context Aware Systems -- 3…Application Contextualization in Memory Support Systems -- 3.1 The Introduction of Time Context -- 3.2 The Introduction of Location Context -- 3.3 Web IntegrationWeb Integration -- 3.4 Integration of Time and Location ContextIntegration of Time and Location Context -- 3.5 Toward a New Generation of Memory Prosthetic DevicesMemory Prosthetic Devices -- 4…The Architecture of Our System -- 4.1 Server Side. , 4.1.1 A Three Tier ArchitectureThree Tier Architecture -- 4.1.2 Reasoning Engine -- 4.2 Client Side -- 5…ExperimentsExperiments and Users' FeedbacksUsers' Feedbacks -- 6…Ontology Management and Enrichment -- 7…Conclusions -- References -- 10 Viable Service Business Models Towards Inter-cooperative Strategies: Conceptual Evolutionary Considerations -- Abstract -- 1…Chronological Development of S-D Logic Model -- 2…The Role of Intangibility-Heterogeneity-Inseparability-Perishability Framework in the Separation of G-D and S-D Logics -- 2.1 IHIP Characteristics and Its Critics -- 2.2 Implications for the Definition of Services -- 3…Service Science Perspectives: Service-Dominant versus Goods-Dominant logic -- 3.1 Resource-Based Definition of Service Logic -- 3.2 S-D Logic and General Theory -- 4…Case Studies of Empirical Applications of S-D Logic -- 4.1 S-D Logic, Branding and Networks -- 4.2 S-D Logic and Discontinuous Innovations -- 4.3 S-D Logic and Co-Produced Knowledge -- 4.4 S-D Logic and Social Construction TheoriesSocial Construction Theories -- 4.5 S-D Logic and Logistics Service ValueLogistics Service Value -- 4.6 S-D Logic and ProcurementProcurement -- 4.7 S-D Logic and Service Experience -- 4.8 S-D Logic and Competitive AdvantageCompetitive Advantage -- 4.9 Cloud ComputingCloud computing as an Illustrative Example of S-D Logic -- 5…Conclusions and Future Work -- References -- 11 Discovering the Hidden Semantics in Enterprise Resource Planning Data Through Formal Concept Analysis -- Abstract -- 1…Introduction -- 1.1 Enterprise Resource Planning Systems -- 1.2 Rationale -- 2…Overview of Analysis -- 2.1 Data Preparation -- 2.2 Analysing Transactional ActivityAnalysis!Transactional Activity -- 2.3 Analysing Transactional Activity with DescriptionsAnalysis!Transactional Activity with Descriptions. , 2.4 Analysing Transactional Activity with Multiple AttributesAnalysis!Multiple Attributes.