Amal El Fallah Seghrouchni is Full Professor at the University of Pierre and Marie Curie, Paris, France where she heads the MAS team at LIP6 (Laboratory of Informatics of Paris 6).Fuyuki Ishikawa is Associate Professor at the National Institute of Informatics (NII), Tokyo, Japan.Laurent Hérault holds a PhD degree in computer science from INPG. Since 2011 he is VP, Director of the Europe division at CEA-LETI and is a CEA fellow since 2014.Hideyuki Tokuda is Professor at the Faculty of Environment and Information Studies and Director of the Ubiquitous Computing and Communication Laboratory at Keio University, Japan.

• Preface  xiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIIntroduction xviiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIChapter 1. Shared Wireless Sensor Networks as Enablers for a Context Management System in Smart Cities  1Kenji TEI1.1. Introduction  11.2. Background 31.3. XAC middleware 51.3.1. Architecture of XAC middleware  61.4. Task-description language  71.4.1. Existing solutions 81.4.2. XAC middleware solutions 101.5. Runtime task management  121.5.1. Existing solutions 121.5.2. XAC middleware solutions 141.6. Self-adaptation 161.6.1. Existing solutions 171.6.2. XAC middleware solutions 171.7. Discussion 181.8. Conclusion 191.9 Bibliography  19Chapter 2. Sensorizer: An Architecture for Regenerating Cyber-physical Data Streams from the Web 23Jin NAKAZAWA2.1. Introduction  232.2. Sensorizer architecture  252.2.1. Sensing process of EWC 252.2.2. Sensorizer architecture  252.3. Implementation  272.3.1. Sensorizer browser extension  272.3.2. Probe  282.3.3. Sensorizer/SoX API 292.4. Case of sensorized smart cities  292.5. Conclusion 322.6. Bibliography  32Chapter 3. Smart Agent Foundations: From Planning to Spatio-temporal Guidance  33Ahmed-Chawki CHAOUCHE, Amal EL FALLAH SEGHROUCHNI, Jean-Michel ILIÉ and Djamel Eddine SAÏDOUNI3.1. Introduction  333.2. Smart-campus: use case and scenario  353.2.1. Smart-campus architecture  363.2.2. Scenario  373.3. Description of the software architecture for a smart ambient agent  373.4. Higher order agent model 383.4.1. Application to the scenario  393.5. Description of the concurrent planner based on AgLOTOS language  403.5.1. Agent plan structure 403.5.2. Syntax of AgLOTOS plans 423.5.3. Building of the agent plan from the intentions 443.5.4. Planning state of the agent  453.6. Contextual planning guidance  453.6.1. Semantics of AgLOTOS plans  463.6.2. Contextual planning system 483.6.3. Application to the scenario  503.7. Spatio-temporal guidance from past experiences  523.7.1. Contextual planning architecture  523.7.2. Learning actions from past experiences 533.7.3. Spatio-temporal guidance  583.8. Conclusion 613.9. Bibliography 62Chapter 4. A Multi-Agent Middleware for Deployment of Ambient Applications 65Ferdinand PIETTE, Amal EL FALLAH SEGHROUCHNI, Patrick TAILLIBERT, Costin CAVAL and CÉDRIC DINONT4.1. Introduction  654.2. Challenges for ambient intelligence and Internet of Things  674.2.1. Toward the heterogeneity of hardware and protocols 674.2.2. Data transport and processing  694.2.3. Management of data privacy 714.3. Deployment of applications for ambient systems  734.3.1. Reasoning about heterogeneity 734.3.2. Graph modeling  744.3.3. Mathematical formalization of the deployment process  764.3.4. Modified graph-matching algorithm  814.3.5. Conclusion 854.4. Multi-agent middleware for ambient systems  864.4.1. Scenario  874.4.2. Multi-agent modeling 884.4.3. Distributed reasoning 924.4.4. Design and implementation 964.5. Conclusion 1024.6. Bibliography  103Chapter 5. ClouT: Cloud of Things for Empowering Citizen’s Clout in Smart Cities 107Kenji TEI, Levent GÜREEN and TAKURO YONEZAWA5.1. Objective of the ClouT project  1075.2. Goal of the ClouT project 1095.3. ClouT concept 1105.3.1. CIaaS concept 1125.3.2. CPaaS concept  1155.3.3. CSaaS concept  1175.4. ClouT reference architecture 1185.4.1. CIaaS components  1185.4.2. CPaaS components  1205.4.3. Security and Dependability components  1215.5. Mapping the architecture 1225.6. Conclusion 1255.7. Bibliography  126Chapter 6. sensiNact IoT Platform as a Service 127Levent GÜRGEN, Christophe MUNILLA, Rémi DRUILHE, Etienne GANDRILLE and Jander BOTELHO DO NASCIMENTO6.1. Introduction  1286.2. State of the art 1306.2.1. IoT solutions architectures  1306.2.2. Existing IoT platforms  1316.3. Architecture and data model 1336.4. Platform security management  1386.5. The sensiNact studio  1406.5.1. Graphical user interface 1416.5.2. Creating applications 1436.5.3. Application deployment 1446.6. Conclusion 1466.7. Bibliography  146Chapter 7. Verification and Configuration of Smart Space Applications  149Fuyuki ISHIKAWA and Shinichi HONIDEN7.1. Introduction  1497.2. Conflicts in smart space applications  1507.2.1. Event-driven control of smart spaces 1507.2.2. Description of event-driven behavior 1517.2.3. Conflicts in event-driven control 1517.2.4. Application of model checking techniques 1537.3. Framework for verifying and configuring smart space applications  1547.3.1. Overview 1547.3.2. Semantic model  1557.3.3. Definition of state transition model 1587.3.4. Properties to verify  1597.3.5. Implementation  1607.3.6. Model checker implementation 1617.4. Case study 1617.4.1. Scenario and initial specification  1617.4.2. Analyzing sound conflicts  1627.4.3. Further scenarios 1647.5. Related work  1647.6. Concluding remarks  1657.7. Acknowledgments 1667.8. Bibliography  166Chapter 8. SmartSantander: A Massive Self-Managed, Scalable and Interconnected IoT Deployment 169José Antonio GALACHE, Juan Ramón SANTANA and Luis MUÑOZ8.1. Introduction  1698.2. SmartSantander: novel architecture for service provision and experimentation 1708.3. SmartSantander deployment: use cases 1738.4. SmartSantander interacting with ClouT 1758.4.1. IoT device naming  1768.4.2. IoT device description  1778.4.3. IoT resource manager 1818.4.4. Virtualization module 1828.5. Conclusions  1848.6. Bibliography  185Chapter 9. Using Context-aware Multi-agent Systems for Robust Smart City Infrastructure 187Andrei OLARU, Adina Magda FLOREA and Amal EL FALLAH SEGHROUCHNI9.1. Introduction  1879.1.1. Smart cities and ambient intelligence  1889.2. Requirements  1899.2.1. Information at the right time 1919.2.2. Robustness, reliability, dependability and trust  1929.2.3. Privacy and personal information  1929.3. Solutions for managing context information  1939.3.1. Related work and projects  1939.3.2. A local solution for a global result 1959.4. MAS-based application-independent middleware 1969.4.1. Architecture  1989.4.2. Generality of the design 2039.4.3. Resilience in case of failures 2039.5. Conclusion 2049.6. Bibliography  204Chapter 10. City of Santander 207Sonia SOTERO MUÑIZ and José Antonio TEIXEIRA VITIENES10.1. Introduction  20710.2. ClouT project 21010.2.1. Participatory sensing for city management 21110.2.2. Traffic mobility management 21510.2.3. Conclusions 21910.3. Bibliography 220Chapter 11. Fujisawa, Towards a Sustainable Smart City 221Takuro YONEZAWA11.1. Introduction 22111.1.1. Sensorized garbage trucks 22211.1.2. Enoshima Info Surfboard  22311.1.3. Smile Coupon  22411.2. Architecture and application domains 22511.2.1. Architecture with ClouT components 22511.2.2. Components for implementation  22611.2.3. Interaction among components 22711.2.4. Development scenario  22811.2.5. Design and implementation 22911.3. Results 23611.4. Conclusion  23711.5. Bibliography 237List of Authors 239Index 241

Amal El Fallah Seghrouchni is Full Professor at the University of Pierre and Marie Curie, Paris, France where she heads the MAS team at LIP6 (Laboratory of Informatics of Paris 6).Fuyuki Ishikawa is Associate Professor at the National Institute of Informatics (NII), Tokyo, Japan.Laurent Hérault holds a PhD degree in computer science from INPG. Since 2011 he is VP, Director of the Europe division at CEA-LETI and is a CEA fellow since 2014.Hideyuki Tokuda is Professor at the Faculty of Environment and Information Studies and Director of the Ubiquitous Computing and Communication Laboratory at Keio University, Japan.

• Preface  xiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIIntroduction xviiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIChapter 1. Shared Wireless Sensor Networks as Enablers for a Context Management System in Smart Cities  1Kenji TEI1.1. Introduction  11.2. Background 31.3. XAC middleware 51.3.1. Architecture of XAC middleware  61.4. Task-description language  71.4.1. Existing solutions 81.4.2. XAC middleware solutions 101.5. Runtime task management  121.5.1. Existing solutions 121.5.2. XAC middleware solutions 141.6. Self-adaptation 161.6.1. Existing solutions 171.6.2. XAC middleware solutions 171.7. Discussion 181.8. Conclusion 191.9 Bibliography  19Chapter 2. Sensorizer: An Architecture for Regenerating Cyber-physical Data Streams from the Web 23Jin NAKAZAWA2.1. Introduction  232.2. Sensorizer architecture  252.2.1. Sensing process of EWC 252.2.2. Sensorizer architecture  252.3. Implementation  272.3.1. Sensorizer browser extension  272.3.2. Probe  282.3.3. Sensorizer/SoX API 292.4. Case of sensorized smart cities  292.5. Conclusion 322.6. Bibliography  32Chapter 3. Smart Agent Foundations: From Planning to Spatio-temporal Guidance  33Ahmed-Chawki CHAOUCHE, Amal EL FALLAH SEGHROUCHNI, Jean-Michel ILIÉ and Djamel Eddine SAÏDOUNI3.1. Introduction  333.2. Smart-campus: use case and scenario  353.2.1. Smart-campus architecture  363.2.2. Scenario  373.3. Description of the software architecture for a smart ambient agent  373.4. Higher order agent model 383.4.1. Application to the scenario  393.5. Description of the concurrent planner based on AgLOTOS language  403.5.1. Agent plan structure 403.5.2. Syntax of AgLOTOS plans 423.5.3. Building of the agent plan from the intentions 443.5.4. Planning state of the agent  453.6. Contextual planning guidance  453.6.1. Semantics of AgLOTOS plans  463.6.2. Contextual planning system 483.6.3. Application to the scenario  503.7. Spatio-temporal guidance from past experiences  523.7.1. Contextual planning architecture  523.7.2. Learning actions from past experiences 533.7.3. Spatio-temporal guidance  583.8. Conclusion 613.9. Bibliography 62Chapter 4. A Multi-Agent Middleware for Deployment of Ambient Applications 65Ferdinand PIETTE, Amal EL FALLAH SEGHROUCHNI, Patrick TAILLIBERT, Costin CAVAL and CÉDRIC DINONT4.1. Introduction  654.2. Challenges for ambient intelligence and Internet of Things  674.2.1. Toward the heterogeneity of hardware and protocols 674.2.2. Data transport and processing  694.2.3. Management of data privacy 714.3. Deployment of applications for ambient systems  734.3.1. Reasoning about heterogeneity 734.3.2. Graph modeling  744.3.3. Mathematical formalization of the deployment process  764.3.4. Modified graph-matching algorithm  814.3.5. Conclusion 854.4. Multi-agent middleware for ambient systems  864.4.1. Scenario  874.4.2. Multi-agent modeling 884.4.3. Distributed reasoning 924.4.4. Design and implementation 964.5. Conclusion 1024.6. Bibliography  103Chapter 5. ClouT: Cloud of Things for Empowering Citizen’s Clout in Smart Cities 107Kenji TEI, Levent GÜREEN and TAKURO YONEZAWA5.1. Objective of the ClouT project  1075.2. Goal of the ClouT project 1095.3. ClouT concept 1105.3.1. CIaaS concept 1125.3.2. CPaaS concept  1155.3.3. CSaaS concept  1175.4. ClouT reference architecture 1185.4.1. CIaaS components  1185.4.2. CPaaS components  1205.4.3. Security and Dependability components  1215.5. Mapping the architecture 1225.6. Conclusion 1255.7. Bibliography  126Chapter 6. sensiNact IoT Platform as a Service 127Levent GÜRGEN, Christophe MUNILLA, Rémi DRUILHE, Etienne GANDRILLE and Jander BOTELHO DO NASCIMENTO6.1. Introduction  1286.2. State of the art 1306.2.1. IoT solutions architectures  1306.2.2. Existing IoT platforms  1316.3. Architecture and data model 1336.4. Platform security management  1386.5. The sensiNact studio  1406.5.1. Graphical user interface 1416.5.2. Creating applications 1436.5.3. Application deployment 1446.6. Conclusion 1466.7. Bibliography  146Chapter 7. Verification and Configuration of Smart Space Applications  149Fuyuki ISHIKAWA and Shinichi HONIDEN7.1. Introduction  1497.2. Conflicts in smart space applications  1507.2.1. Event-driven control of smart spaces 1507.2.2. Description of event-driven behavior 1517.2.3. Conflicts in event-driven control 1517.2.4. Application of model checking techniques 1537.3. Framework for verifying and configuring smart space applications  1547.3.1. Overview 1547.3.2. Semantic model  1557.3.3. Definition of state transition model 1587.3.4. Properties to verify  1597.3.5. Implementation  1607.3.6. Model checker implementation 1617.4. Case study 1617.4.1. Scenario and initial specification  1617.4.2. Analyzing sound conflicts  1627.4.3. Further scenarios 1647.5. Related work  1647.6. Concluding remarks  1657.7. Acknowledgments 1667.8. Bibliography  166Chapter 8. SmartSantander: A Massive Self-Managed, Scalable and Interconnected IoT Deployment 169José Antonio GALACHE, Juan Ramón SANTANA and Luis MUÑOZ8.1. Introduction  1698.2. SmartSantander: novel architecture for service provision and experimentation 1708.3. SmartSantander deployment: use cases 1738.4. SmartSantander interacting with ClouT 1758.4.1. IoT device naming  1768.4.2. IoT device description  1778.4.3. IoT resource manager 1818.4.4. Virtualization module 1828.5. Conclusions  1848.6. Bibliography  185Chapter 9. Using Context-aware Multi-agent Systems for Robust Smart City Infrastructure 187Andrei OLARU, Adina Magda FLOREA and Amal EL FALLAH SEGHROUCHNI9.1. Introduction  1879.1.1. Smart cities and ambient intelligence  1889.2. Requirements  1899.2.1. Information at the right time 1919.2.2. Robustness, reliability, dependability and trust  1929.2.3. Privacy and personal information  1929.3. Solutions for managing context information  1939.3.1. Related work and projects  1939.3.2. A local solution for a global result 1959.4. MAS-based application-independent middleware 1969.4.1. Architecture  1989.4.2. Generality of the design 2039.4.3. Resilience in case of failures 2039.5. Conclusion 2049.6. Bibliography  204Chapter 10. City of Santander 207Sonia SOTERO MUÑIZ and José Antonio TEIXEIRA VITIENES10.1. Introduction  20710.2. ClouT project 21010.2.1. Participatory sensing for city management 21110.2.2. Traffic mobility management 21510.2.3. Conclusions 21910.3. Bibliography 220Chapter 11. Fujisawa, Towards a Sustainable Smart City 221Takuro YONEZAWA11.1. Introduction 22111.1.1. Sensorized garbage trucks 22211.1.2. Enoshima Info Surfboard  22311.1.3. Smile Coupon  22411.2. Architecture and application domains 22511.2.1. Architecture with ClouT components 22511.2.2. Components for implementation  22611.2.3. Interaction among components 22711.2.4. Development scenario  22811.2.5. Design and implementation 22911.3. Results 23611.4. Conclusion  23711.5. Bibliography 237List of Authors 239Index 241

Amal El Fallah Seghrouchni is Full Professor at the University of Pierre and Marie Curie, Paris, France where she heads the MAS team at LIP6 (Laboratory of Informatics of Paris 6).Fuyuki Ishikawa is Associate Professor at the National Institute of Informatics (NII), Tokyo, Japan.Laurent Hérault holds a PhD degree in computer science from INPG. Since 2011 he is VP, Director of the Europe division at CEA-LETI and is a CEA fellow since 2014.Hideyuki Tokuda is Professor at the Faculty of Environment and Information Studies and Director of the Ubiquitous Computing and Communication Laboratory at Keio University, Japan.

• Preface  xiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIIntroduction xviiAmal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEIChapter 1. Shared Wireless Sensor Networks as Enablers for a Context Management System in Smart Cities  1Kenji TEI1.1. Introduction  11.2. Background 31.3. XAC middleware 51.3.1. Architecture of XAC middleware  61.4. Task-description language  71.4.1. Existing solutions 81.4.2. XAC middleware solutions 101.5. Runtime task management  121.5.1. Existing solutions 121.5.2. XAC middleware solutions 141.6. Self-adaptation 161.6.1. Existing solutions 171.6.2. XAC middleware solutions 171.7. Discussion 181.8. Conclusion 191.9 Bibliography  19Chapter 2. Sensorizer: An Architecture for Regenerating Cyber-physical Data Streams from the Web 23Jin NAKAZAWA2.1. Introduction  232.2. Sensorizer architecture  252.2.1. Sensing process of EWC 252.2.2. Sensorizer architecture  252.3. Implementation  272.3.1. Sensorizer browser extension  272.3.2. Probe  282.3.3. Sensorizer/SoX API 292.4. Case of sensorized smart cities  292.5. Conclusion 322.6. Bibliography  32Chapter 3. Smart Agent Foundations: From Planning to Spatio-temporal Guidance  33Ahmed-Chawki CHAOUCHE, Amal EL FALLAH SEGHROUCHNI, Jean-Michel ILIÉ and Djamel Eddine SAÏDOUNI3.1. Introduction  333.2. Smart-campus: use case and scenario  353.2.1. Smart-campus architecture  363.2.2. Scenario  373.3. Description of the software architecture for a smart ambient agent  373.4. Higher order agent model 383.4.1. Application to the scenario  393.5. Description of the concurrent planner based on AgLOTOS language  403.5.1. Agent plan structure 403.5.2. Syntax of AgLOTOS plans 423.5.3. Building of the agent plan from the intentions 443.5.4. Planning state of the agent  453.6. Contextual planning guidance  453.6.1. Semantics of AgLOTOS plans  463.6.2. Contextual planning system 483.6.3. Application to the scenario  503.7. Spatio-temporal guidance from past experiences  523.7.1. Contextual planning architecture  523.7.2. Learning actions from past experiences 533.7.3. Spatio-temporal guidance  583.8. Conclusion 613.9. Bibliography 62Chapter 4. A Multi-Agent Middleware for Deployment of Ambient Applications 65Ferdinand PIETTE, Amal EL FALLAH SEGHROUCHNI, Patrick TAILLIBERT, Costin CAVAL and CÉDRIC DINONT4.1. Introduction  654.2. Challenges for ambient intelligence and Internet of Things  674.2.1. Toward the heterogeneity of hardware and protocols 674.2.2. Data transport and processing  694.2.3. Management of data privacy 714.3. Deployment of applications for ambient systems  734.3.1. Reasoning about heterogeneity 734.3.2. Graph modeling  744.3.3. Mathematical formalization of the deployment process  764.3.4. Modified graph-matching algorithm  814.3.5. Conclusion 854.4. Multi-agent middleware for ambient systems  864.4.1. Scenario  874.4.2. Multi-agent modeling 884.4.3. Distributed reasoning 924.4.4. Design and implementation 964.5. Conclusion 1024.6. Bibliography  103Chapter 5. ClouT: Cloud of Things for Empowering Citizen’s Clout in Smart Cities 107Kenji TEI, Levent GÜREEN and TAKURO YONEZAWA5.1. Objective of the ClouT project  1075.2. Goal of the ClouT project 1095.3. ClouT concept 1105.3.1. CIaaS concept 1125.3.2. CPaaS concept  1155.3.3. CSaaS concept  1175.4. ClouT reference architecture 1185.4.1. CIaaS components  1185.4.2. CPaaS components  1205.4.3. Security and Dependability components  1215.5. Mapping the architecture 1225.6. Conclusion 1255.7. Bibliography  126Chapter 6. sensiNact IoT Platform as a Service 127Levent GÜRGEN, Christophe MUNILLA, Rémi DRUILHE, Etienne GANDRILLE and Jander BOTELHO DO NASCIMENTO6.1. Introduction  1286.2. State of the art 1306.2.1. IoT solutions architectures  1306.2.2. Existing IoT platforms  1316.3. Architecture and data model 1336.4. Platform security management  1386.5. The sensiNact studio  1406.5.1. Graphical user interface 1416.5.2. Creating applications 1436.5.3. Application deployment 1446.6. Conclusion 1466.7. Bibliography  146Chapter 7. Verification and Configuration of Smart Space Applications  149Fuyuki ISHIKAWA and Shinichi HONIDEN7.1. Introduction  1497.2. Conflicts in smart space applications  1507.2.1. Event-driven control of smart spaces 1507.2.2. Description of event-driven behavior 1517.2.3. Conflicts in event-driven control 1517.2.4. Application of model checking techniques 1537.3. Framework for verifying and configuring smart space applications  1547.3.1. Overview 1547.3.2. Semantic model  1557.3.3. Definition of state transition model 1587.3.4. Properties to verify  1597.3.5. Implementation  1607.3.6. Model checker implementation 1617.4. Case study 1617.4.1. Scenario and initial specification  1617.4.2. Analyzing sound conflicts  1627.4.3. Further scenarios 1647.5. Related work  1647.6. Concluding remarks  1657.7. Acknowledgments 1667.8. Bibliography  166Chapter 8. SmartSantander: A Massive Self-Managed, Scalable and Interconnected IoT Deployment 169José Antonio GALACHE, Juan Ramón SANTANA and Luis MUÑOZ8.1. Introduction  1698.2. SmartSantander: novel architecture for service provision and experimentation 1708.3. SmartSantander deployment: use cases 1738.4. SmartSantander interacting with ClouT 1758.4.1. IoT device naming  1768.4.2. IoT device description  1778.4.3. IoT resource manager 1818.4.4. Virtualization module 1828.5. Conclusions  1848.6. Bibliography  185Chapter 9. Using Context-aware Multi-agent Systems for Robust Smart City Infrastructure 187Andrei OLARU, Adina Magda FLOREA and Amal EL FALLAH SEGHROUCHNI9.1. Introduction  1879.1.1. Smart cities and ambient intelligence  1889.2. Requirements  1899.2.1. Information at the right time 1919.2.2. Robustness, reliability, dependability and trust  1929.2.3. Privacy and personal information  1929.3. Solutions for managing context information  1939.3.1. Related work and projects  1939.3.2. A local solution for a global result 1959.4. MAS-based application-independent middleware 1969.4.1. Architecture  1989.4.2. Generality of the design 2039.4.3. Resilience in case of failures 2039.5. Conclusion 2049.6. Bibliography  204Chapter 10. City of Santander 207Sonia SOTERO MUÑIZ and José Antonio TEIXEIRA VITIENES10.1. Introduction  20710.2. ClouT project 21010.2.1. Participatory sensing for city management 21110.2.2. Traffic mobility management 21510.2.3. Conclusions 21910.3. Bibliography 220Chapter 11. Fujisawa, Towards a Sustainable Smart City 221Takuro YONEZAWA11.1. Introduction 22111.1.1. Sensorized garbage trucks 22211.1.2. Enoshima Info Surfboard  22311.1.3. Smile Coupon  22411.2. Architecture and application domains 22511.2.1. Architecture with ClouT components 22511.2.2. Components for implementation  22611.2.3. Interaction among components 22711.2.4. Development scenario  22811.2.5. Design and implementation 22911.3. Results 23611.4. Conclusion  23711.5. Bibliography 237List of Authors 239Index 241