Pubbl/distr/stampa	Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica	1 online resource (512 pages)
Disciplina	006.22
Collana	Internet of Things, Technology, Communications and Computing
Soggetto topico	Cooperating objects (Computer systems)
ISBN	3-030-87059-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910523799903321

Edizione	[1st edition]
Pubbl/distr/stampa	Hoboken, N.J., : Wiley, 2011
Descrizione fisica	1 online resource (674 p.)
Disciplina	004.67/8
Altri autori (Persone)	BuyyaRajkumar <1970-> BrobergJames GoscinskiAndrzej
Collana	Wiley Series on Parallel and Distributed Computing
Soggetto topico	Cloud computing
ISBN	1-283-02569-8 9786613025692 1-118-00220-2 0-470-94010-7 0-470-94009-3
Classificazione	COM014000
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	pt. 1. Foundations -- pt. 2. Infrastructure as a service (IAAS) -- pt. 3. Platform and software as a service (PAAS/IAAS) -- pt. 4. Monitoring and management -- pt. 5 Applications -- pt. 6. Governance and case studies.
Record Nr.	UNINA-9910141049503321

Pubbl/distr/stampa	[Place of publication not identified], : Conference Publishing Services, 2007
Soggetto topico	Computational grids (Computer systems) Engineering & Applied Sciences Computer Science
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNISA-996198934903316

Edizione	[1st edition]
Pubbl/distr/stampa	Hoboken, New Jersey : , : John Wiley & Sons, Inc., , 2019
Descrizione fisica	1 online resource (515 pages)
Disciplina	004.6782
Collana	Wiley series on parallel and distributed computing
Soggetto topico	Cloud computing Electronic data processing - Distributed processing
Soggetto genere / forma	Electronic books.
ISBN	1-119-52508-X 1-119-52501-2
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	List of Contributors xix -- Preface xxiii -- Acknowledgments xxvii -- Part I Foundations 1 -- 1 Internet of Things (IoT) and New Computing Paradigms 3 / Chii Chang, Satish Narayana Srirama, and Rajkumar Buyya -- 1.1 Introduction 3 -- 1.2 Relevant Technologies 6 -- 1.3 Fog and Edge Computing Completing the Cloud 8 -- 1.3.1 Advantages of FEC: SCALE 8 -- 1.3.2 How FEC AchievesThese Advantages: SCANC 9 -- 1.4 Hierarchy of Fog and Edge Computing 13 -- 1.5 Business Models 16 -- 1.6 Opportunities and Challenges 17 -- 1.7 Conclusions 20 -- References 21 -- 2 Addressing the Challenges in Federating Edge Resources 25 / Ahmet Cihat Baktir, Cagatay Sonmez, CemErsoy, Atay Ozgovde, and Blesson Varghese -- 2.1 Introduction 25 -- 2.2 The Networking Challenge 27 -- 2.3 The Management Challenge 34 -- 2.4 Miscellaneous Challenges 40 -- 2.5 Conclusions 45 -- References 45 -- 3 Integrating IoT + Fog + Cloud Infrastructures: System Modeling and Research Challenges 51 / Guto Leoni Santos,Matheus Ferreira, Leylane Ferreira, Judith Kelner, Djamel Sadok, Edison Albuquerque, Theo Lynn, and Patricia Takako Endo -- 3.1 Introduction 51 -- 3.2 Methodology 52 -- 3.3 Integrated C2F2T Literature by Modeling Technique 55 -- 3.4 Integrated C2F2T Literature by Use-Case Scenarios 65 -- 3.5 Integrated C2F2T Literature by Metrics 68 -- 3.6 Future Research Directions 72 -- 3.7 Conclusions 73 -- Acknowledgments 74 -- References 75 -- 4 Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds 79 / Adel Nadjaran Toosi, RedowanMahmud, Qinghua Chi, and Rajkumar Buyya -- 4.1 Introduction 79 -- 4.2 Background 80 -- 4.3 Network Slicing in 5G 83 -- 4.4 Network Slicing in Software-Defined Clouds 87 -- 4.5 Network Slicing Management in Edge and Fog 91 -- 4.6 Future Research Directions 93 -- 4.7 Conclusions 96 -- Acknowledgments 96 -- References 96 -- 5 Optimization Problems in Fog and Edge Computing 103 / Zoltán Ádám Mann -- 5.1 Introduction 103 -- 5.2 Background / RelatedWork 104. 5.3 Preliminaries 105 -- 5.4 The Case for Optimization in Fog Computing 107 -- 5.5 Formal Modeling Framework for Fog Computing 108 -- 5.6 Metrics 109 -- 5.6.5 Further Quality Attributes 112 -- 5.7 Optimization Opportunities along the Fog Architecture 113 -- 5.8 Optimization Opportunities along the Service Life Cycle 114 -- 5.9 Toward a Taxonomy of Optimization Problems in Fog Computing 115 -- 5.10 Optimization Techniques 117 -- 5.11 Future Research Directions 118 -- 5.12 Conclusions 119 -- Acknowledgments 119 -- References 119 -- Part II Middlewares 123 -- 6 Middleware for Fog and Edge Computing: Design Issues 125 / Madhurima Pore, Vinaya Chakati, Ayan Banerjee, and Sandeep K. S. Gupta -- 6.1 Introduction 125 -- 6.2 Need for Fog and Edge Computing Middleware 126 -- 6.3 Design Goals 126 -- 6.4 State-of-the-Art Middleware Infrastructures 128 -- 6.5 System Model 129 -- 6.6 Proposed Architecture 131 -- 6.7 Case Study Example 136 -- 6.8 Future Research Directions 137 -- 6.9 Conclusions 139 -- References 139 -- 7 A Lightweight Container Middleware for Edge Cloud Architectures 145 / David von Leon, LorenzoMiori, Julian Sanin, Nabil El Ioini, Sven Helmer, and Claus Pahl -- 7.1 Introduction 145 -- 7.2 Background/RelatedWork 146 -- 7.3 Clusters for Lightweight Edge Clouds 149 -- 7.4 Architecture Management - Storage and Orchestration 152 -- 7.5 IoT Integration 159 -- 7.6 Security Management for Edge Cloud Architectures 159 -- 7.7 Future Research Directions 165 -- 7.8 Conclusions 166 -- References 167 -- 8 Data Management in Fog Computing 171 / Tina Samizadeh Nikoui, Amir Masoud Rahmani, and Hooman Tabarsaied -- 8.1 Introduction 171 -- 8.2 Background 172 -- 8.3 Fog Data Management 174 -- 8.4 Future Research and Direction 186 -- 8.5 Conclusions 186 -- References 188 -- 9 Predictive Analysis to Support Fog Application Deployment 191 / Antonio Brogi, Stefano Forti, and Ahmad Ibrahim -- 9.1 Introduction 191 -- 9.2 Motivating Example: Smart Building 193 -- 9.3 Predictive Analysis with FogTorch 197. 9.4 Motivating Example (continued) 206 -- 9.5 Related Work 207 -- 9.6 Future Research Directions 214 -- 9.7 Conclusions 216 -- References 217 -- 10 Using Machine Learning for Protecting the Security and Privacy of Internet of Things (IoT) Systems 223 / Melody Moh and Robinson Raju -- 10.1 Introduction 223 -- 10.2 Background 234 -- 10.3 Survey of ML Techniques for Defending IoT Devices 242 -- 10.4 Machine Learning in Fog Computing 248 -- 10.4.1 Introduction 248 -- 10.5 Future Research Directions 252 -- 10.6 Conclusions 252 -- References 253 -- Part III Applications and Issues 259 -- 11 Fog Computing Realization for Big Data Analytics 261 / Farhad Mehdipour, Bahman Javadi, AniketMahanti, and Guillermo Ramirez-Prado -- 11.1 Introduction 261 -- 11.2 Big Data Analytics 262 -- 11.3 Data Analytics in the Fog 267 -- 11.4 Prototypes and Evaluation 272 -- 11.4.1 Architecture 272 -- 11.4.2 Configurations 274 -- 11.5 Case Studies 277 -- 11.6 Related Work 282 -- 11.7 Future Research Directions 287 -- 11.8 Conclusions 287 -- References 288 -- 12 Exploiting Fog Computing in Health Monitoring 291 / Tuan Nguyen Gia and Mingzhe Jiang -- 12.1 Introduction 291 -- 12.2 An Architecture of a Health Monitoring IoT-Based System with Fog Computing 293 -- 12.3 Fog Computing Services in Smart E-Health Gateways 297 -- 12.4 System Implementation 304 -- 12.5 Case Studies, Experimental Results, and Evaluation 308 -- 12.6 Discussion of Connected Components 313 -- 12.7 Related Applications in Fog Computing 313 -- 12.8 Future Research Directions 314 -- 12.9 Conclusions 314 -- References 315 -- 13 Smart Surveillance Video Stream Processing at the Edge for Real-Time Human Objects Tracking 319 / Seyed Yahya Nikouei, Ronghua Xu, and Yu Chen -- 13.1 Introduction 319 -- 13.2 Human Object Detection 320 -- 13.3 Object Tracking 327 -- 13.4 Lightweight Human Detection 335 -- 13.5 Case Study 337 -- 13.6 Future Research Directions 342 -- 13.7 Conclusions 343 -- References 343 -- 14 Fog Computing Model for Evolving Smart Transportation Applications 347 / M. Muzakkir Hussain,Mohammad Saad Alam, and M.M. Sufyan Beg. 14.1 Introduction 347 -- 14.2 Data-Driven Intelligent Transportation Systems 348 -- 14.3 Mission-Critical Computing Requirements of Smart Transportation Applications 351 -- 14.4 Fog Computing for Smart Transportation Applications 354 -- 14.5 Case Study: Intelligent Traffic Lights Management (ITLM) System 359 -- 14.6 Fog Orchestration Challenges and Future Directions 362 -- 14.7 Future Research Directions 364 -- 14.8 Conclusions 369 -- References 370 -- 15 Testing Perspectives of Fog-Based IoT Applications 373 / Priyanka Chawla and Rohit Chawla -- 15.1 Introduction 373 -- 15.2 Background 374 -- 15.3 Testing Perspectives 376 -- 15.4 Future Research Directions 393 -- 15.5 Conclusions 405 -- References 406 -- 16 Legal Aspects of Operating IoT Applications in the Fog 411 / G. Gultekin Varkonyi, Sz. Varadi, and Attila Kertesz -- 16.1 Introduction 411 -- 16.2 RelatedWork 412 -- 16.3 Classification of Fog/Edge/IoT Applications 413 -- 16.4 Restrictions of the GDPR Affecting Cloud, Fog, and IoT Applications 414 -- 16.5 Data Protection by Design Principles 425 -- 16.6 Future Research Directions 430 -- 16.7 Conclusions 430 -- Acknowledgment 431 -- References 431 -- 17 Modeling and Simulation of Fog and Edge Computing Environments Using iFogSim Toolkit 433 / Redowan Mahmud and Rajkumar Buyya -- 17.1 Introduction 433 -- 17.2 iFogSim Simulator and Its Components 435 -- 17.3 Installation of iFogSim 436 -- 17.4 Building Simulation with iFogSim 437 -- 17.5 Example Scenarios 438 -- 17.6 Simulation of a Placement Policy 450 -- 17.7 A Case Study in Smart Healthcare 461 -- 17.8 Conclusions 463 -- References 464 -- Index 467.
Record Nr.	UNINA-9910467745103321

Edizione	[1st edition]
Pubbl/distr/stampa	Hoboken, New Jersey : , : John Wiley & Sons, Inc., , 2019
Descrizione fisica	1 online resource (515 pages)
Disciplina	004.6782
Collana	Wiley series on parallel and distributed computing THEi Wiley ebooks.
Soggetto topico	Cloud computing Electronic data processing - Distributed processing
ISBN	1-119-52506-3 1-119-52508-X 1-119-52501-2
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	List of Contributors xix -- Preface xxiii -- Acknowledgments xxvii -- Part I Foundations 1 -- 1 Internet of Things (IoT) and New Computing Paradigms 3 / Chii Chang, Satish Narayana Srirama, and Rajkumar Buyya -- 1.1 Introduction 3 -- 1.2 Relevant Technologies 6 -- 1.3 Fog and Edge Computing Completing the Cloud 8 -- 1.3.1 Advantages of FEC: SCALE 8 -- 1.3.2 How FEC AchievesThese Advantages: SCANC 9 -- 1.4 Hierarchy of Fog and Edge Computing 13 -- 1.5 Business Models 16 -- 1.6 Opportunities and Challenges 17 -- 1.7 Conclusions 20 -- References 21 -- 2 Addressing the Challenges in Federating Edge Resources 25 / Ahmet Cihat Baktir, Cagatay Sonmez, CemErsoy, Atay Ozgovde, and Blesson Varghese -- 2.1 Introduction 25 -- 2.2 The Networking Challenge 27 -- 2.3 The Management Challenge 34 -- 2.4 Miscellaneous Challenges 40 -- 2.5 Conclusions 45 -- References 45 -- 3 Integrating IoT + Fog + Cloud Infrastructures: System Modeling and Research Challenges 51 / Guto Leoni Santos,Matheus Ferreira, Leylane Ferreira, Judith Kelner, Djamel Sadok, Edison Albuquerque, Theo Lynn, and Patricia Takako Endo -- 3.1 Introduction 51 -- 3.2 Methodology 52 -- 3.3 Integrated C2F2T Literature by Modeling Technique 55 -- 3.4 Integrated C2F2T Literature by Use-Case Scenarios 65 -- 3.5 Integrated C2F2T Literature by Metrics 68 -- 3.6 Future Research Directions 72 -- 3.7 Conclusions 73 -- Acknowledgments 74 -- References 75 -- 4 Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds 79 / Adel Nadjaran Toosi, RedowanMahmud, Qinghua Chi, and Rajkumar Buyya -- 4.1 Introduction 79 -- 4.2 Background 80 -- 4.3 Network Slicing in 5G 83 -- 4.4 Network Slicing in Software-Defined Clouds 87 -- 4.5 Network Slicing Management in Edge and Fog 91 -- 4.6 Future Research Directions 93 -- 4.7 Conclusions 96 -- Acknowledgments 96 -- References 96 -- 5 Optimization Problems in Fog and Edge Computing 103 / Zoltán Ádám Mann -- 5.1 Introduction 103 -- 5.2 Background / RelatedWork 104. 5.3 Preliminaries 105 -- 5.4 The Case for Optimization in Fog Computing 107 -- 5.5 Formal Modeling Framework for Fog Computing 108 -- 5.6 Metrics 109 -- 5.6.5 Further Quality Attributes 112 -- 5.7 Optimization Opportunities along the Fog Architecture 113 -- 5.8 Optimization Opportunities along the Service Life Cycle 114 -- 5.9 Toward a Taxonomy of Optimization Problems in Fog Computing 115 -- 5.10 Optimization Techniques 117 -- 5.11 Future Research Directions 118 -- 5.12 Conclusions 119 -- Acknowledgments 119 -- References 119 -- Part II Middlewares 123 -- 6 Middleware for Fog and Edge Computing: Design Issues 125 / Madhurima Pore, Vinaya Chakati, Ayan Banerjee, and Sandeep K. S. Gupta -- 6.1 Introduction 125 -- 6.2 Need for Fog and Edge Computing Middleware 126 -- 6.3 Design Goals 126 -- 6.4 State-of-the-Art Middleware Infrastructures 128 -- 6.5 System Model 129 -- 6.6 Proposed Architecture 131 -- 6.7 Case Study Example 136 -- 6.8 Future Research Directions 137 -- 6.9 Conclusions 139 -- References 139 -- 7 A Lightweight Container Middleware for Edge Cloud Architectures 145 / David von Leon, LorenzoMiori, Julian Sanin, Nabil El Ioini, Sven Helmer, and Claus Pahl -- 7.1 Introduction 145 -- 7.2 Background/RelatedWork 146 -- 7.3 Clusters for Lightweight Edge Clouds 149 -- 7.4 Architecture Management - Storage and Orchestration 152 -- 7.5 IoT Integration 159 -- 7.6 Security Management for Edge Cloud Architectures 159 -- 7.7 Future Research Directions 165 -- 7.8 Conclusions 166 -- References 167 -- 8 Data Management in Fog Computing 171 / Tina Samizadeh Nikoui, Amir Masoud Rahmani, and Hooman Tabarsaied -- 8.1 Introduction 171 -- 8.2 Background 172 -- 8.3 Fog Data Management 174 -- 8.4 Future Research and Direction 186 -- 8.5 Conclusions 186 -- References 188 -- 9 Predictive Analysis to Support Fog Application Deployment 191 / Antonio Brogi, Stefano Forti, and Ahmad Ibrahim -- 9.1 Introduction 191 -- 9.2 Motivating Example: Smart Building 193 -- 9.3 Predictive Analysis with FogTorch 197. 9.4 Motivating Example (continued) 206 -- 9.5 Related Work 207 -- 9.6 Future Research Directions 214 -- 9.7 Conclusions 216 -- References 217 -- 10 Using Machine Learning for Protecting the Security and Privacy of Internet of Things (IoT) Systems 223 / Melody Moh and Robinson Raju -- 10.1 Introduction 223 -- 10.2 Background 234 -- 10.3 Survey of ML Techniques for Defending IoT Devices 242 -- 10.4 Machine Learning in Fog Computing 248 -- 10.4.1 Introduction 248 -- 10.5 Future Research Directions 252 -- 10.6 Conclusions 252 -- References 253 -- Part III Applications and Issues 259 -- 11 Fog Computing Realization for Big Data Analytics 261 / Farhad Mehdipour, Bahman Javadi, AniketMahanti, and Guillermo Ramirez-Prado -- 11.1 Introduction 261 -- 11.2 Big Data Analytics 262 -- 11.3 Data Analytics in the Fog 267 -- 11.4 Prototypes and Evaluation 272 -- 11.4.1 Architecture 272 -- 11.4.2 Configurations 274 -- 11.5 Case Studies 277 -- 11.6 Related Work 282 -- 11.7 Future Research Directions 287 -- 11.8 Conclusions 287 -- References 288 -- 12 Exploiting Fog Computing in Health Monitoring 291 / Tuan Nguyen Gia and Mingzhe Jiang -- 12.1 Introduction 291 -- 12.2 An Architecture of a Health Monitoring IoT-Based System with Fog Computing 293 -- 12.3 Fog Computing Services in Smart E-Health Gateways 297 -- 12.4 System Implementation 304 -- 12.5 Case Studies, Experimental Results, and Evaluation 308 -- 12.6 Discussion of Connected Components 313 -- 12.7 Related Applications in Fog Computing 313 -- 12.8 Future Research Directions 314 -- 12.9 Conclusions 314 -- References 315 -- 13 Smart Surveillance Video Stream Processing at the Edge for Real-Time Human Objects Tracking 319 / Seyed Yahya Nikouei, Ronghua Xu, and Yu Chen -- 13.1 Introduction 319 -- 13.2 Human Object Detection 320 -- 13.3 Object Tracking 327 -- 13.4 Lightweight Human Detection 335 -- 13.5 Case Study 337 -- 13.6 Future Research Directions 342 -- 13.7 Conclusions 343 -- References 343 -- 14 Fog Computing Model for Evolving Smart Transportation Applications 347 / M. Muzakkir Hussain,Mohammad Saad Alam, and M.M. Sufyan Beg. 14.1 Introduction 347 -- 14.2 Data-Driven Intelligent Transportation Systems 348 -- 14.3 Mission-Critical Computing Requirements of Smart Transportation Applications 351 -- 14.4 Fog Computing for Smart Transportation Applications 354 -- 14.5 Case Study: Intelligent Traffic Lights Management (ITLM) System 359 -- 14.6 Fog Orchestration Challenges and Future Directions 362 -- 14.7 Future Research Directions 364 -- 14.8 Conclusions 369 -- References 370 -- 15 Testing Perspectives of Fog-Based IoT Applications 373 / Priyanka Chawla and Rohit Chawla -- 15.1 Introduction 373 -- 15.2 Background 374 -- 15.3 Testing Perspectives 376 -- 15.4 Future Research Directions 393 -- 15.5 Conclusions 405 -- References 406 -- 16 Legal Aspects of Operating IoT Applications in the Fog 411 / G. Gultekin Varkonyi, Sz. Varadi, and Attila Kertesz -- 16.1 Introduction 411 -- 16.2 RelatedWork 412 -- 16.3 Classification of Fog/Edge/IoT Applications 413 -- 16.4 Restrictions of the GDPR Affecting Cloud, Fog, and IoT Applications 414 -- 16.5 Data Protection by Design Principles 425 -- 16.6 Future Research Directions 430 -- 16.7 Conclusions 430 -- Acknowledgment 431 -- References 431 -- 17 Modeling and Simulation of Fog and Edge Computing Environments Using iFogSim Toolkit 433 / Redowan Mahmud and Rajkumar Buyya -- 17.1 Introduction 433 -- 17.2 iFogSim Simulator and Its Components 435 -- 17.3 Installation of iFogSim 436 -- 17.4 Building Simulation with iFogSim 437 -- 17.5 Example Scenarios 438 -- 17.6 Simulation of a Placement Policy 450 -- 17.7 A Case Study in Smart Healthcare 461 -- 17.8 Conclusions 463 -- References 464 -- Index 467.
Record Nr.	UNINA-9910537424603321