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Achieving Digital Transformation Using Hybrid Cloud : Design Standardized Next-Generation Applications for Any Infrastructure
Achieving Digital Transformation Using Hybrid Cloud : Design Standardized Next-Generation Applications for Any Infrastructure
Autore Grover Vikas
Edizione [1st ed.]
Pubbl/distr/stampa Birmingham : , : Packt Publishing, Limited, , 2023
Descrizione fisica 1 online resource (234 pages)
Disciplina 004.67/82
Altri autori (Persone) VermaIshu
RajagopalanPraveen
Soggetto topico Cloud computing
Storage area networks (Computer networks)
ISBN 9781837634156
1837634157
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright and Credits -- Contributors -- About the reviewers -- Table of Contents -- Preface -- Part 1: Containers, Kubernetes, and DevOps for Hybrid Cloud -- Chapter 1: Adopting the Right Strategy for Building a Hybrid Cloud -- Exploring cloud computing -- types and service delivery models -- Defining the hybrid cloud -- Variations in the hybrid cloud -- homogeneous and heterogeneous -- Hybrid cloud use cases -- Understanding the benefits of hybrid cloud computing -- Hybrid cloud strategies -- Addressing compliance considerations -- Automating security measures
Finding the right balance between public and private clouds -- Evaluating available tools and technologies -- Summary -- Further reading -- Chapter 2: Dealing with VMs, Containers, and Kubernetes -- Introduction to VM and containers -- VMs -- Containers -- Anatomy of containers -- About OCI and Docker -- The differences between VMs and containers -- Container orchestration -- Why do we need container orchestration? -- Kubernetes -- a container orchestration tool -- OpenShift -- AWS EKS -- Azure Kubernetes Service (AKS) -- VMware Tanzu Kubernetes Grid (TKG) -- HashiCorp Nomad
Google Kubernetes Engine (GKE) -- Docker Swarm -- CI/CD on the hybrid cloud -- Summary -- Further reading -- Chapter 3: Provisioning Infrastructure with IaC -- Infrastructure provisioning overview -- Virtualizing hardware with SDI -- Provisioning IaaS -- Provisioning and managing infrastructure with IaC -- Imperative and declarative frameworks -- Imperative and declarative framework tools for IaC -- Considerations for IaC -- Accelerating IT service delivery with DevOps -- CI/CD -- Continuous testing -- Continuous operations -- Monitoring and observability
Automating delivery and deployment with GitOps -- Push versus pull deployments -- Enabling GitOps using Argo CD -- Best practices for GitOps -- Summary -- Further reading -- Chapter 4: Communicating across Kubernetes -- Pod design patterns -- The sidecar pattern -- The adapter pattern -- The ambassador pattern -- Container-to-container communication -- Pod-to-pod communication -- Pods with multiple interfaces -- Pod-to-service communication -- External-to-service communication -- How to discover pods and services -- How to publish services -- How to stitch multiple K8s clusters
Submariner -- using layer 3 networking -- Skupper -- using a common application network (layer 7) -- Service meshes -- Federation of service meshes -- Summary -- Further reading -- Part 2: Design Patterns, DevOps, and GitOps -- Chapter 5: Design Patterns for Telcos and Industrial Sectors -- Applying design patterns for operational excellence -- Telco -- Creating your own pattern -- Defining a framework -- Cloud-friendly -- A common application platform -- Consistent management -- Automation -- Summary -- Further reading -- Chapter 6: Securing the Hybrid Cloud
Record Nr. UNINA-9911007151903321
Grover Vikas  
Birmingham : , : Packt Publishing, Limited, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced content delivery, streaming, and cloud services / / edited by, Mukaddim Pathan, Telstra Corporation Ltd., Australia, Ramesh K. Sitaraman, University of Massachusetts, Amherst and Akamai Technologies, USA, Dom Robinson, id3as-Company Ltd., UK
Advanced content delivery, streaming, and cloud services / / edited by, Mukaddim Pathan, Telstra Corporation Ltd., Australia, Ramesh K. Sitaraman, University of Massachusetts, Amherst and Akamai Technologies, USA, Dom Robinson, id3as-Company Ltd., UK
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2014]
Descrizione fisica 1 online resource (1105 p.)
Disciplina 004.67/82
Altri autori (Persone) PathanMukaddim
SitaramanRamesh Kumar <1964->
RobinsonDom
Collana Wiley series on parallel and distributed computing
Soggetto topico Cloud computing
Computer networks
ISBN 1-118-90964-X
1-118-90969-0
1-118-90970-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xv -- Acknowledgments xxi -- Contributors xxiii -- PART I CDN AND MEDIA STREAMING BASICS 1 -- 1 CLOUD-BASED CONTENT DELIVERY AND STREAMING 3 /Mukaddim Pathan -- 1.1 Introduction 3 -- 1.2 CDN Overview 5 -- 1.3 Workings of a CDN 10 -- 1.4 CDN Trends 21 -- 1.5 Research Issues 28 -- 1.6 Conclusion 29 -- References 29 -- 2 LIVE STREAMING ECOSYSTEMS 33 /Dom Robinson -- 2.1 Introduction 33 -- 2.2 Live Streaming Pre-Evolution 34 -- 2.3 Live, Linear, Nonlinear 35 -- 2.4 Media Streaming 37 -- 2.5 Related Network Models 38 -- 2.6 Streaming Protocol Success 43 -- 2.7 Platform Divergence and Codec Convergence 44 -- 2.8 Adaptive Bitrate (ABR) Streaming 45 -- 2.9 Internet Radio and HTTP 48 -- 2.10 Conclusion 48 -- References 49 -- 3 PRACTICAL SYSTEMS FOR LIVE STREAMING 51 /Dom Robinson -- 3.1 Introduction 51 -- 3.2 Common Concepts in Live Streaming 52 -- 3.3 The Practicals 56 -- 3.4 Conclusion 69 -- References 70 -- 4 EFFICIENCY OF CACHING AND CONTENT DELIVERY IN BROADBAND ACCESS NETWORKS 71 /Gerhard Haslinger -- 4.1 Introduction 71 -- 4.2 Options and Properties for Web Caching 73 -- 4.3 Zipf Laws for Requests to Popular Content 75 -- 4.4 Efficiency and Performance Modeling for Caches 76 -- 4.5 Effect of Replacement Strategies on Cache Hit Rates 78 -- 4.6 Replacement Methods Based on Request Statistics 81 -- 4.7 Global CDN and P2P Overlays for Content Delivery 84 -- 4.8 Summary and Conclusion 86 -- Acknowledgments 87 -- References 87 -- 5 ANYCAST REQUEST ROUTING FOR CONTENT DELIVERY NETWORKS 91 /Hussein A. Alzoubi, Michael Rabinovich, Seungjoon Lee, Kobus Van Der Merwe, and Oliver Spatscheck -- 5.1 Introduction 91 -- 5.2 CDN Request Routing: An Overview 93 -- 5.3 A Practical Load-Aware IP Anycast CDN 96 -- 5.4 Mapping Algorithms 98 -- 5.5 Evaluation 102 -- 5.6 IPv6 Anycast CDNs 107 -- 5.7 Discussion and Open Questions 114 -- 5.8 Conclusion 116 -- References 116 -- 6 CLOUD-BASED CONTENT DELIVERY TO HOME ECOSYSTEMS 119 /Tiago Cruz, Paulo Sim̃oes, and Edmundo Monteiro -- 6.1 Introduction 119.
6.2 Bringing Cloud Services to Home: State of the Art 120 -- 6.3 Virtualizing the Access Network Infrastructure 123 -- 6.4 Virtualization for Cloud Service Delivery to Home 130 -- 6.5 Future Trends 137 -- 6.6 Summary and Conclusion 137 -- Acknowledgments 137 -- References 138 -- 7 MOBILE VIDEO STREAMING 141 /Ram Lakshmi Narayanan, Yinghua Ye, Anuj Kaul, and Mili Shah -- 7.1 Introduction 141 -- 7.2 Mobile Broadband Architecture 142 -- 7.3 Video Streaming Protocols 143 -- 7.4 Video Optimization Services 146 -- 7.5 Operator-Hosted CDN 149 -- 7.6 Cloud-Based Video Streaming 151 -- 7.7 Future Research Directions 154 -- Acknowledgments 156 -- References 156 -- PART II CDN PERFORMANCE MANAGEMENT AND OPTIMIZATION 159 -- 8 CDN ANALYTICS: A PRIMER 161 /Timothy Siglin -- 8.1 Introduction 161 -- 8.2 Why Measure? 162 -- 8.3 What do we Measure? 162 -- 8.4 What about Business Intelligence? 169 -- 8.5 Measuring Stateless Delivery 171 -- 8.6 Billing Analytics 173 -- 8.7 CDN Analytics Tools 174 -- 8.8 Recent Trends in CDN Analytics 175 -- 8.9 Conclusion 176 -- References 176 -- 9 CDN MODELING 179 /Tolga Bektas and Ozgur Ercetin -- 9.1 Introduction 179 -- 9.2 Basics on Mathematical Modeling and Optimization 180 -- 9.3 Video-on-Demand Applications 182 -- 9.4 Optimization Problems in Content Delivery and VoD Services 185 -- 9.5 Visionary Thoughts for Practitioners 198 -- 9.6 Future Research Directions 198 -- 9.7 Conclusions 199 -- Acknowledgments 200 -- References 200 -- 10 ANALYZING CONTENT DELIVERY NETWORKS 203 /Benjamin Molina, Jaime Calvo, Carlos E. Palau, and Manuel Esteve -- 10.1 Introduction 203 -- 10.2 Previous Work 204 -- 10.3 Basic CDN Model 205 -- 10.4 Enhancing the Model 206 -- 10.5 Performance Evaluation 212 -- 10.6 Conclusions 216 -- References 216 -- 11 MULTISOURCE STREAM AGGREGATION IN THE CLOUD 219 /Marat Zhanikeev -- 11.1 Introduction 219 -- 11.2 Terminologies 221 -- 11.3 Background and Related Work 222 -- 11.4 The Substream Method in the Cloud 224 -- 11.5 Stream Aggregation in the Cloud 226.
11.6 Models 228 -- 11.7 Analysis 231 -- 11.8 Visionary Thoughts for Practitioners 236 -- 11.9 Future Research Directions 238 -- 11.10 Conclusion 239 -- References 239 -- 12 BEYOND CDN: CONTENT PROCESSING AT THE EDGE OF THE CLOUD 243 /Salekul Islam and Jean-Charles Gŕegoire -- 12.1 Introduction 243 -- 12.2 Existing Content Delivery Platforms 244 -- 12.3 Comparison of Existing Content Delivery Platforms 247 -- 12.4 An Edge Cloud-Based Model 251 -- 12.5 Results and Insights 255 -- 12.6 Future Research Directions 256 -- 12.7 Conclusion 257 -- References 257 -- 13 DYNAMIC RECONFIGURATION FOR ADAPTIVE STREAMING 259 /Norihiko Yoshida -- 13.1 Introduction 259 -- 13.2 Background and Related Work 260 -- 13.3 Dynamic Server Deployment 262 -- 13.4 From Content Delivery to Streaming 263 -- 13.5 Future Research Directions 267 -- 13.6 Conclusion 269 -- Acknowledgments 269 -- References 269 -- 14 MINING DISTRIBUTED DATA STREAMS ON CONTENT DELIVERY NETWORKS 273 /Eugenio Cesario, Carlo Mastroianni, and Domenico Talia -- 14.1 Introduction 273 -- 14.2 Background and Related Work 275 -- 14.3 A Hybrid Multidomain Architecture 277 -- 14.4 A Prototype for Stream Mining in a CDN 281 -- 14.5 Visionary Thoughts for Practitioners 285 -- 14.6 Future Research Directions 285 -- 14.7 Conclusion 286 -- References 286 -- 15 CDN CAPACITY PLANNING 289 /Phil Davies and Mukaddim Pathan -- 15.1 Introduction 289 -- 15.2 Capacity Planning Process 290 -- 15.3 Undertaking the Capacity Planning Process 295 -- 15.4 CDN Capacity Planning Case Study 300 -- 15.5 Recent Developments and Challenges 302 -- 15.6 Summary and Conclusion 303 -- References 303 -- PART III CASE STUDIES AND NEXT GENERATION CDNs 305 -- 16 OVERLAY NETWORKS: AN AKAMAI PERSPECTIVE 307 /Ramesh K. Sitaraman, Mangesh Kasbekar, Woody Lichtenstein, and Manish Jain -- 16.1 Introduction 307 -- 16.2 Background 309 -- 16.3 Caching Overlays 314 -- 16.4 Routing Overlays 318 -- 16.5 Security Overlays 323 -- 16.6 Conclusion 325 -- References 326 -- 17 NEXT-GENERATION CDNs: A CoBlitz PERSPECTIVE 329 /Vivek S. Pai.
17.1 Introduction 329 -- 17.2 Carrier CDNs 331 -- 17.3 Managed CDNs 332 -- 17.4 Federated CDNs 333 -- 17.5 Licensed CDNs 335 -- 17.6 Case Study: CoBlitz 337 -- 17.7 CoBlitz Commercialization 343 -- 17.8 Implications of HTTP Adaptive Streaming 345 -- 17.9 CoBlitz Commercialization Lessons 347 -- 17.10 CDN Industry Directions 348 -- Acknowledgments 349 -- References 349 -- 18 CONTENT DELIVERY IN CHINA: A ChinaCache PERSPECTIVE 353 /Michael Talyansky, Alexei Tumarkin, Hunter Xu, and Ken Zhang -- 18.1 Introduction 353 -- 18.2 Content-Aware Network Services in China 356 -- 18.3 Directions for Future CDN Research and Trends in China 365 -- 18.4 Conclusion 366 -- References 366 -- 19 PlatonTV: A SCIENTIFIC HIGH DEFINITION CONTENT DELIVERY PLATFORM 369 /Mirosław Czyrnek, Jedrzej Jajor, Jerzy Jamrozy, Ewa Kusmierek, Cezary Mazurek, Maciej Stroinski, and Jan Weglarz -- 19.1 Introduction 369 -- 19.2 Background and Related Work 371 -- 19.3 PlatonTV Architecture 372 -- 19.4 Content Ingest 374 -- 19.5 Content Distribution and Management 376 -- 19.6 Content Delivery 379 -- 19.7 Availability and Reliability 381 -- 19.8 Visionary Thoughts for Practitioners 382 -- 19.9 Future Research Directions 383 -- 19.10 Conclusion 383 -- Acknowledgments 383 -- References 384 -- 20 CacheCast: A SINGLE-SOURCE MULTIPLE-DESTINATION CACHING MECHANISM 385 /Piotr Srebrny, Dag H.L. Sorbo, Thomas Plagemann, Vera Goebel, and Andreas Mauthe -- 20.1 Introduction 385 -- 20.2 Related Work 387 -- 20.3 CacheCast Overview 388 -- 20.4 Background on Multidestination Traffic 389 -- 20.5 CacheCast Design 391 -- 20.6 CacheCast Efficiency 396 -- 20.7 CacheCast Applications 399 -- 20.8 Visionary Thoughts for Practitioners 407 -- 20.9 Future Research Directions 409 -- 20.10 Conclusion 409 -- Acknowledgments 410 -- References 410 -- 21 CONTENT REPLICATION AND DELIVERY IN INFORMATION-CENTRIC NETWORKS 413 /Vasilis Sourlas, Paris Flegkas, Dimitrios Katsaros, and Leandros Tassiulas -- 21.1 Introduction 413 -- 21.2 Related Work 414.
21.3 Framework for Information Replication in ICN 416 -- 21.4 Performance Evaluation 423 -- 21.5 Future Research Directions 426 -- 21.6 Conclusion 426 -- Acknowledgments 427 -- References 427 -- 22 ROBUST CONTENT BROADCASTING IN VEHICULAR NETWORKS 431 /Giancarlo Fortino, Carlos T. Calafate, Juan C. Cano, and Pietro Manzoni -- 22.1 Introduction 431 -- 22.2 Vehicular Networks 432 -- 22.3 Forward Error Correction Techniques 433 -- 22.4 A Robust Broadcast-Based Content Delivery System 434 -- 22.5 CDS Simulation in NS-3 436 -- 22.6 Performance Evaluation 437 -- 22.7 Future Research Trends 444 -- 22.8 Summary and Conclusion 446 -- Acknowledgments 447 -- References 447 -- 23 ON THE IMPACT OF ONLINE SOCIAL NETWORKS IN CONTENT DELIVERY 449 /Irene Kilanioti, Chryssis Georgiou, and George Pallis -- 23.1 Introduction 449 -- 23.2 Online Social Networks Background 450 -- 23.3 Characterization of Social Cascades 453 -- 23.4 Online Social Network Measurements 456 -- 23.5 Systems 458 -- 23.6 Future Research Directions 459 -- 23.7 Conclusion 461 -- Acknowledgments 461 -- References 461 -- Index 465.
Record Nr. UNINA-9910132165103321
Hoboken, New Jersey : , : Wiley, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced content delivery, streaming, and cloud services / / edited by, Mukaddim Pathan, Telstra Corporation Ltd., Australia, Ramesh K. Sitaraman, University of Massachusetts, Amherst and Akamai Technologies, USA, Dom Robinson, id3as-Company Ltd., UK
Advanced content delivery, streaming, and cloud services / / edited by, Mukaddim Pathan, Telstra Corporation Ltd., Australia, Ramesh K. Sitaraman, University of Massachusetts, Amherst and Akamai Technologies, USA, Dom Robinson, id3as-Company Ltd., UK
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2014]
Descrizione fisica 1 online resource (1105 p.)
Disciplina 004.67/82
Altri autori (Persone) PathanMukaddim
SitaramanRamesh Kumar <1964->
RobinsonDom
Collana Wiley series on parallel and distributed computing
Soggetto topico Cloud computing
Computer networks
ISBN 1-118-90964-X
1-118-90969-0
1-118-90970-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xv -- Acknowledgments xxi -- Contributors xxiii -- PART I CDN AND MEDIA STREAMING BASICS 1 -- 1 CLOUD-BASED CONTENT DELIVERY AND STREAMING 3 /Mukaddim Pathan -- 1.1 Introduction 3 -- 1.2 CDN Overview 5 -- 1.3 Workings of a CDN 10 -- 1.4 CDN Trends 21 -- 1.5 Research Issues 28 -- 1.6 Conclusion 29 -- References 29 -- 2 LIVE STREAMING ECOSYSTEMS 33 /Dom Robinson -- 2.1 Introduction 33 -- 2.2 Live Streaming Pre-Evolution 34 -- 2.3 Live, Linear, Nonlinear 35 -- 2.4 Media Streaming 37 -- 2.5 Related Network Models 38 -- 2.6 Streaming Protocol Success 43 -- 2.7 Platform Divergence and Codec Convergence 44 -- 2.8 Adaptive Bitrate (ABR) Streaming 45 -- 2.9 Internet Radio and HTTP 48 -- 2.10 Conclusion 48 -- References 49 -- 3 PRACTICAL SYSTEMS FOR LIVE STREAMING 51 /Dom Robinson -- 3.1 Introduction 51 -- 3.2 Common Concepts in Live Streaming 52 -- 3.3 The Practicals 56 -- 3.4 Conclusion 69 -- References 70 -- 4 EFFICIENCY OF CACHING AND CONTENT DELIVERY IN BROADBAND ACCESS NETWORKS 71 /Gerhard Haslinger -- 4.1 Introduction 71 -- 4.2 Options and Properties for Web Caching 73 -- 4.3 Zipf Laws for Requests to Popular Content 75 -- 4.4 Efficiency and Performance Modeling for Caches 76 -- 4.5 Effect of Replacement Strategies on Cache Hit Rates 78 -- 4.6 Replacement Methods Based on Request Statistics 81 -- 4.7 Global CDN and P2P Overlays for Content Delivery 84 -- 4.8 Summary and Conclusion 86 -- Acknowledgments 87 -- References 87 -- 5 ANYCAST REQUEST ROUTING FOR CONTENT DELIVERY NETWORKS 91 /Hussein A. Alzoubi, Michael Rabinovich, Seungjoon Lee, Kobus Van Der Merwe, and Oliver Spatscheck -- 5.1 Introduction 91 -- 5.2 CDN Request Routing: An Overview 93 -- 5.3 A Practical Load-Aware IP Anycast CDN 96 -- 5.4 Mapping Algorithms 98 -- 5.5 Evaluation 102 -- 5.6 IPv6 Anycast CDNs 107 -- 5.7 Discussion and Open Questions 114 -- 5.8 Conclusion 116 -- References 116 -- 6 CLOUD-BASED CONTENT DELIVERY TO HOME ECOSYSTEMS 119 /Tiago Cruz, Paulo Sim̃oes, and Edmundo Monteiro -- 6.1 Introduction 119.
6.2 Bringing Cloud Services to Home: State of the Art 120 -- 6.3 Virtualizing the Access Network Infrastructure 123 -- 6.4 Virtualization for Cloud Service Delivery to Home 130 -- 6.5 Future Trends 137 -- 6.6 Summary and Conclusion 137 -- Acknowledgments 137 -- References 138 -- 7 MOBILE VIDEO STREAMING 141 /Ram Lakshmi Narayanan, Yinghua Ye, Anuj Kaul, and Mili Shah -- 7.1 Introduction 141 -- 7.2 Mobile Broadband Architecture 142 -- 7.3 Video Streaming Protocols 143 -- 7.4 Video Optimization Services 146 -- 7.5 Operator-Hosted CDN 149 -- 7.6 Cloud-Based Video Streaming 151 -- 7.7 Future Research Directions 154 -- Acknowledgments 156 -- References 156 -- PART II CDN PERFORMANCE MANAGEMENT AND OPTIMIZATION 159 -- 8 CDN ANALYTICS: A PRIMER 161 /Timothy Siglin -- 8.1 Introduction 161 -- 8.2 Why Measure? 162 -- 8.3 What do we Measure? 162 -- 8.4 What about Business Intelligence? 169 -- 8.5 Measuring Stateless Delivery 171 -- 8.6 Billing Analytics 173 -- 8.7 CDN Analytics Tools 174 -- 8.8 Recent Trends in CDN Analytics 175 -- 8.9 Conclusion 176 -- References 176 -- 9 CDN MODELING 179 /Tolga Bektas and Ozgur Ercetin -- 9.1 Introduction 179 -- 9.2 Basics on Mathematical Modeling and Optimization 180 -- 9.3 Video-on-Demand Applications 182 -- 9.4 Optimization Problems in Content Delivery and VoD Services 185 -- 9.5 Visionary Thoughts for Practitioners 198 -- 9.6 Future Research Directions 198 -- 9.7 Conclusions 199 -- Acknowledgments 200 -- References 200 -- 10 ANALYZING CONTENT DELIVERY NETWORKS 203 /Benjamin Molina, Jaime Calvo, Carlos E. Palau, and Manuel Esteve -- 10.1 Introduction 203 -- 10.2 Previous Work 204 -- 10.3 Basic CDN Model 205 -- 10.4 Enhancing the Model 206 -- 10.5 Performance Evaluation 212 -- 10.6 Conclusions 216 -- References 216 -- 11 MULTISOURCE STREAM AGGREGATION IN THE CLOUD 219 /Marat Zhanikeev -- 11.1 Introduction 219 -- 11.2 Terminologies 221 -- 11.3 Background and Related Work 222 -- 11.4 The Substream Method in the Cloud 224 -- 11.5 Stream Aggregation in the Cloud 226.
11.6 Models 228 -- 11.7 Analysis 231 -- 11.8 Visionary Thoughts for Practitioners 236 -- 11.9 Future Research Directions 238 -- 11.10 Conclusion 239 -- References 239 -- 12 BEYOND CDN: CONTENT PROCESSING AT THE EDGE OF THE CLOUD 243 /Salekul Islam and Jean-Charles Gŕegoire -- 12.1 Introduction 243 -- 12.2 Existing Content Delivery Platforms 244 -- 12.3 Comparison of Existing Content Delivery Platforms 247 -- 12.4 An Edge Cloud-Based Model 251 -- 12.5 Results and Insights 255 -- 12.6 Future Research Directions 256 -- 12.7 Conclusion 257 -- References 257 -- 13 DYNAMIC RECONFIGURATION FOR ADAPTIVE STREAMING 259 /Norihiko Yoshida -- 13.1 Introduction 259 -- 13.2 Background and Related Work 260 -- 13.3 Dynamic Server Deployment 262 -- 13.4 From Content Delivery to Streaming 263 -- 13.5 Future Research Directions 267 -- 13.6 Conclusion 269 -- Acknowledgments 269 -- References 269 -- 14 MINING DISTRIBUTED DATA STREAMS ON CONTENT DELIVERY NETWORKS 273 /Eugenio Cesario, Carlo Mastroianni, and Domenico Talia -- 14.1 Introduction 273 -- 14.2 Background and Related Work 275 -- 14.3 A Hybrid Multidomain Architecture 277 -- 14.4 A Prototype for Stream Mining in a CDN 281 -- 14.5 Visionary Thoughts for Practitioners 285 -- 14.6 Future Research Directions 285 -- 14.7 Conclusion 286 -- References 286 -- 15 CDN CAPACITY PLANNING 289 /Phil Davies and Mukaddim Pathan -- 15.1 Introduction 289 -- 15.2 Capacity Planning Process 290 -- 15.3 Undertaking the Capacity Planning Process 295 -- 15.4 CDN Capacity Planning Case Study 300 -- 15.5 Recent Developments and Challenges 302 -- 15.6 Summary and Conclusion 303 -- References 303 -- PART III CASE STUDIES AND NEXT GENERATION CDNs 305 -- 16 OVERLAY NETWORKS: AN AKAMAI PERSPECTIVE 307 /Ramesh K. Sitaraman, Mangesh Kasbekar, Woody Lichtenstein, and Manish Jain -- 16.1 Introduction 307 -- 16.2 Background 309 -- 16.3 Caching Overlays 314 -- 16.4 Routing Overlays 318 -- 16.5 Security Overlays 323 -- 16.6 Conclusion 325 -- References 326 -- 17 NEXT-GENERATION CDNs: A CoBlitz PERSPECTIVE 329 /Vivek S. Pai.
17.1 Introduction 329 -- 17.2 Carrier CDNs 331 -- 17.3 Managed CDNs 332 -- 17.4 Federated CDNs 333 -- 17.5 Licensed CDNs 335 -- 17.6 Case Study: CoBlitz 337 -- 17.7 CoBlitz Commercialization 343 -- 17.8 Implications of HTTP Adaptive Streaming 345 -- 17.9 CoBlitz Commercialization Lessons 347 -- 17.10 CDN Industry Directions 348 -- Acknowledgments 349 -- References 349 -- 18 CONTENT DELIVERY IN CHINA: A ChinaCache PERSPECTIVE 353 /Michael Talyansky, Alexei Tumarkin, Hunter Xu, and Ken Zhang -- 18.1 Introduction 353 -- 18.2 Content-Aware Network Services in China 356 -- 18.3 Directions for Future CDN Research and Trends in China 365 -- 18.4 Conclusion 366 -- References 366 -- 19 PlatonTV: A SCIENTIFIC HIGH DEFINITION CONTENT DELIVERY PLATFORM 369 /Mirosław Czyrnek, Jedrzej Jajor, Jerzy Jamrozy, Ewa Kusmierek, Cezary Mazurek, Maciej Stroinski, and Jan Weglarz -- 19.1 Introduction 369 -- 19.2 Background and Related Work 371 -- 19.3 PlatonTV Architecture 372 -- 19.4 Content Ingest 374 -- 19.5 Content Distribution and Management 376 -- 19.6 Content Delivery 379 -- 19.7 Availability and Reliability 381 -- 19.8 Visionary Thoughts for Practitioners 382 -- 19.9 Future Research Directions 383 -- 19.10 Conclusion 383 -- Acknowledgments 383 -- References 384 -- 20 CacheCast: A SINGLE-SOURCE MULTIPLE-DESTINATION CACHING MECHANISM 385 /Piotr Srebrny, Dag H.L. Sorbo, Thomas Plagemann, Vera Goebel, and Andreas Mauthe -- 20.1 Introduction 385 -- 20.2 Related Work 387 -- 20.3 CacheCast Overview 388 -- 20.4 Background on Multidestination Traffic 389 -- 20.5 CacheCast Design 391 -- 20.6 CacheCast Efficiency 396 -- 20.7 CacheCast Applications 399 -- 20.8 Visionary Thoughts for Practitioners 407 -- 20.9 Future Research Directions 409 -- 20.10 Conclusion 409 -- Acknowledgments 410 -- References 410 -- 21 CONTENT REPLICATION AND DELIVERY IN INFORMATION-CENTRIC NETWORKS 413 /Vasilis Sourlas, Paris Flegkas, Dimitrios Katsaros, and Leandros Tassiulas -- 21.1 Introduction 413 -- 21.2 Related Work 414.
21.3 Framework for Information Replication in ICN 416 -- 21.4 Performance Evaluation 423 -- 21.5 Future Research Directions 426 -- 21.6 Conclusion 426 -- Acknowledgments 427 -- References 427 -- 22 ROBUST CONTENT BROADCASTING IN VEHICULAR NETWORKS 431 /Giancarlo Fortino, Carlos T. Calafate, Juan C. Cano, and Pietro Manzoni -- 22.1 Introduction 431 -- 22.2 Vehicular Networks 432 -- 22.3 Forward Error Correction Techniques 433 -- 22.4 A Robust Broadcast-Based Content Delivery System 434 -- 22.5 CDS Simulation in NS-3 436 -- 22.6 Performance Evaluation 437 -- 22.7 Future Research Trends 444 -- 22.8 Summary and Conclusion 446 -- Acknowledgments 447 -- References 447 -- 23 ON THE IMPACT OF ONLINE SOCIAL NETWORKS IN CONTENT DELIVERY 449 /Irene Kilanioti, Chryssis Georgiou, and George Pallis -- 23.1 Introduction 449 -- 23.2 Online Social Networks Background 450 -- 23.3 Characterization of Social Cascades 453 -- 23.4 Online Social Network Measurements 456 -- 23.5 Systems 458 -- 23.6 Future Research Directions 459 -- 23.7 Conclusion 461 -- Acknowledgments 461 -- References 461 -- Index 465.
Record Nr. UNINA-9910823771403321
Hoboken, New Jersey : , : Wiley, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Architecting the cloud : design decisions for cloud computing service models (SaaS, PaaS, and IaaS) / / Michael Kavis
Architecting the cloud : design decisions for cloud computing service models (SaaS, PaaS, and IaaS) / / Michael Kavis
Autore Kavis Michael
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , 2014
Descrizione fisica 1 online resource (351 pages)
Disciplina 004.67/82
Collana Wiley CIO Series
Soggetto topico Information technology - Management
Cloud computing
Computer architecture
ISBN 1-118-82627-2
1-118-69177-6
1-118-82646-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1: Why Cloud, Why Now? -- Chapter 2: Cloud Service Models -- Chapter 3: Cloud Computing Worst Practices -- Chapter 4: It Starts with Architecture -- Chapter 5: Choosing the Right Cloud Service Model -- Chapter 6: The Key to the Cloud: RESTful Services -- Chapter 7: Auditing in the Cloud -- Chapter 8: Data Considerations in the Cloud -- Chapter 9: Security Design in the Cloud -- Chapter 10: Creating a Centralized Logging Strategy -- Chapter 11: SLA Management -- Chapter 12: Monitoring Strategies -- Chapter 13: Disaster Recovery Planning -- Chapter 14: Leveraging a DevOps Culture to Deliver Software Faster and More Reliably -- Chapter 15: Assessing the Organizational Impact of the Cloud Model -- Chapter 16: Final Thoughts
Record Nr. UNINA-9910140290703321
Kavis Michael  
Hoboken, New Jersey : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Architecting the cloud : design decisions for cloud computing service models (SaaS, PaaS, and IaaS) / / Michael Kavis
Architecting the cloud : design decisions for cloud computing service models (SaaS, PaaS, and IaaS) / / Michael Kavis
Autore Kavis Michael
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , 2014
Descrizione fisica 1 online resource (351 pages)
Disciplina 004.67/82
Collana Wiley CIO Series
Soggetto topico Information technology - Management
Cloud computing
Computer architecture
ISBN 1-118-82627-2
1-118-69177-6
1-118-82646-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1: Why Cloud, Why Now? -- Chapter 2: Cloud Service Models -- Chapter 3: Cloud Computing Worst Practices -- Chapter 4: It Starts with Architecture -- Chapter 5: Choosing the Right Cloud Service Model -- Chapter 6: The Key to the Cloud: RESTful Services -- Chapter 7: Auditing in the Cloud -- Chapter 8: Data Considerations in the Cloud -- Chapter 9: Security Design in the Cloud -- Chapter 10: Creating a Centralized Logging Strategy -- Chapter 11: SLA Management -- Chapter 12: Monitoring Strategies -- Chapter 13: Disaster Recovery Planning -- Chapter 14: Leveraging a DevOps Culture to Deliver Software Faster and More Reliably -- Chapter 15: Assessing the Organizational Impact of the Cloud Model -- Chapter 16: Final Thoughts
Record Nr. UNINA-9910826305703321
Kavis Michael  
Hoboken, New Jersey : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Assured cloud computing / / edited by Roy H. Campbell, Charles A. Kamhoua, Kevin A. Kwiat
Assured cloud computing / / edited by Roy H. Campbell, Charles A. Kamhoua, Kevin A. Kwiat
Autore Campbell Roy
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : IEEE Computer Society, Inc./Wiley, , 2018
Descrizione fisica 1 online resource (363 pages)
Disciplina 004.67/82
Soggetto topico Cloud computing
ISBN 1-119-42850-5
1-119-42848-3
1-119-42849-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xiii -- Editors’ Biographies xvii -- List of Contributors xix -- 1 Introduction 1 /Roy H. Campbell -- 1.1 Introduction 1 -- 1.1.1 Mission-Critical Cloud Solutions for the Military 2 -- 1.2 Overview of the Book 3 -- 2 Survivability: Design, Formal Modeling, and Validation of Cloud Storage Systems Using Maude 10 /Rakesh Bobba, Jon Grov, Indranil Gupta, Si Liu, José Meseguer,Peter Csaba Ölveczky, and Stephen Skeirik -- 2.1 Introduction 10 -- 2.1.1 State of the Art 11 -- 2.1.2 Vision: Formal Methods for Cloud Storage Systems 12 -- 2.1.3 The Rewriting Logic Framework 13 -- 2.1.4 Summary: Using Formal Methods on Cloud Storage Systems 15 -- 2.2 Apache Cassandra 17 -- 2.3 Formalizing, Analyzing, and Extending Google’s Megastore 23 -- 2.3.1 Specifying Megastore 23 -- 2.3.2 Analyzing Megastore 25 -- 2.3.2.1 Megastore-CGC 29 -- 2.4 RAMP Transaction Systems 30 -- 2.5 Group Key Management via ZooKeeper 31 -- 2.5.1 ZooKeeper Background 32 -- 2.5.2 System Design 33 -- 2.5.3 Maude Model 34 -- 2.5.4 Analysis and Discussion 35 -- 2.6 How Amazon Web Services Uses Formal Methods 37 -- 2.6.1 Use of Formal Methods 37 -- 2.6.2 Outcomes and Experiences 38 -- 2.6.3 Limitations 39 -- 2.7 Related Work 40 -- 2.8 Concluding Remarks 42 -- 2.8.1 The Future 43 -- 3 Risks and Benefits: Game-Theoretical Analysis and Algorithm for Virtual Machine Security Management in the Cloud 49 /Luke Kwiat, Charles A. Kamhoua, Kevin A. Kwiat, and Jian Tang -- 3.1 Introduction 49 -- 3.2 Vision: Using Cloud Technology in Missions 51 -- 3.3 State of the Art 54 -- 3.4 System Model 57 -- 3.5 Game Model 59 -- 3.6 Game Analysis 61 -- 3.7 Model Extension and Discussion 67 -- 3.8 Numerical Results and Analysis 71 -- 3.8.1 Changes in User 2’s Payoff with Respect to L2 71 -- 3.8.2 Changes in User 2’s Payoff with Respect to e 72 -- 3.8.3 Changes in User 2’s Payoff with Respect to π 73 -- 3.8.4 Changes in User 2’s Payoff with Respect to qI 74 -- 3.8.5 Model Extension to n = 10 Users 75.
3.9 The Future 78 -- 4 Detection and Security: Achieving Resiliency by Dynamic and Passive System Monitoring and Smart Access Control 81 /Zbigniew Kalbarczyk -- 4.1 Introduction 82 -- 4.2 Vision: Using Cloud Technology in Missions 83 -- 4.3 State of the Art 84 -- 4.4 Dynamic VM Monitoring Using Hypervisor Probes 85 -- 4.4.1 Design 86 -- 4.4.2 Prototype Implementation 88 -- 4.4.3 Example Detectors 90 -- 4.4.3.1 Emergency Exploit Detector 90 -- 4.4.3.2 Application Heartbeat Detector 91 -- 4.4.4 Performance 93 -- 4.4.4.1 Microbenchmarks 93 -- 4.4.4.2 Detector Performance 94 -- 4.4.5 Summary 95 -- 4.5 Hypervisor Introspection: A Technique for Evading Passive Virtual Machine Monitoring 96 -- 4.5.1 Hypervisor Introspection 97 -- 4.5.1.1 VMI Monitor 97 -- 4.5.1.2 VM Suspend Side-Channel 97 -- 4.5.1.3 Limitations of Hypervisor Introspection 98 -- 4.5.2 Evading VMI with Hypervisor Introspection 98 -- 4.5.2.1 Insider Attack Model and Assumptions 98 -- 4.5.2.2 Large File Transfer 99 -- 4.5.3 Defenses against Hypervisor Introspection 101 -- 4.5.3.1 Introducing Noise to VM Clocks 101 -- 4.5.3.2 Scheduler-Based Defenses 101 -- 4.5.3.3 Randomized Monitoring Interval 102 -- 4.5.4 Summary 103 -- 4.6 Identifying Compromised Users in Shared Computing Infrastructures 103 -- 4.6.1 Target System and Security Data 104 -- 4.6.1.1 Data and Alerts 105 -- 4.6.1.2 Automating the Analysis of Alerts 106 -- 4.6.2 Overview of the Data 107 -- 4.6.3 Approach 109 -- 4.6.3.1 The Model: Bayesian Network 109 -- 4.6.3.2 Training of the Bayesian Network 110 -- 4.6.4 Analysis of the Incidents 112 -- 4.6.4.1 Sample Incident 112 -- 4.6.4.2 Discussion 113 -- 4.6.5 Supporting Decisions with the Bayesian Network Approach 114 -- 4.6.5.1 Analysis of the Incidents 114 -- 4.6.5.2 Analysis of the Borderline Cases 116 -- 4.6.6 Conclusion 118 -- 4.7 Integrating Attribute-Based Policies into Role-Based Access Control 118 -- 4.7.1 Framework Description 119 -- 4.7.2 Aboveground Level: Tables 119 -- 4.7.2.1 Environment 120.
4.7.2.2 User-Role Assignments 120 -- 4.7.2.3 Role-Permission Assignments 121 -- 4.7.3 Underground Level: Policies 121 -- 4.7.3.1 Role-Permission Assignment Policy 122 -- 4.7.3.2 User-Role Assignment Policy 123 -- 4.7.4 Case Study: Large-Scale ICS 123 -- 4.7.4.1 RBAC Model-Building Process 124 -- 4.7.4.2 Discussion of Case Study 127 -- 4.7.5 Concluding Remarks 128 -- 4.8 The Future 128 -- 5 Scalability, Workloads, and Performance: Replication, Popularity, Modeling, and Geo-Distributed File Stores 133 /Roy H. Campbell, Shadi A. Noghabi, and Cristina L. Abad -- 5.1 Introduction 133 -- 5.2 Vision: Using Cloud Technology in Missions 134 -- 5.3 State of the Art 136 -- 5.4 Data Replication in a Cloud File System 137 -- 5.4.1 MapReduce Clusters 138 -- 5.4.1.1 File Popularity, Temporal Locality, and Arrival Patterns 142 -- 5.4.1.2 Synthetic Workloads for Big Data 144 -- 5.4.2 Related Work 147 -- 5.4.3 Contribution from Our Approach to Generating Big Data Request Streams Using Clustered Renewal Processes 149 -- 5.4.3.1 Scalable Geo-Distributed Storage 149 -- 5.4.4 Related Work 151 -- 5.4.5 Summary of Ambry 152 -- 5.5 Summary 153 -- 5.6 The Future 153 -- 6 Resource Management: Performance Assuredness in Distributed Cloud Computing via Online Reconfigurations 160 /Mainak Ghosh, Le Xu, and Indranil Gupta -- 6.1 Introduction 161 -- 6.2 Vision: Using Cloud Technology in Missions 163 -- 6.3 State of the Art 164 -- 6.3.1 State of the Art: Reconfigurations in Sharded Databases/Storage 164 -- 6.3.1.1 Database Reconfigurations 164 -- 6.3.1.2 Live Migration 164 -- 6.3.1.3 Network Flow Scheduling 164 -- 6.3.2 State of the Art: Scale-Out/Scale-In in Distributed Stream Processing Systems 165 -- 6.3.2.1 Real-Time Reconfigurations 165 -- 6.3.2.2 Live Migration 165 -- 6.3.2.3 Real-Time Elasticity 165 -- 6.3.3 State of the Art: Scale-Out/Scale-In in Distributed Graph Processing Systems 166 -- 6.3.3.1 Data Centers 166 -- 6.3.3.2 Cloud and Storage Systems 166 -- 6.3.3.3 Data Processing Frameworks 166.
6.3.3.4 Partitioning in Graph Processing 166 -- 6.3.3.5 Dynamic Repartitioning in Graph Processing 167 -- 6.3.4 State of the Art: Priorities and Deadlines in Batch Processing Systems 167 -- 6.3.4.1 OS Mechanisms 167 -- 6.3.4.2 Preemption 167 -- 6.3.4.3 Real-Time Scheduling 168 -- 6.3.4.4 Fairness 168 -- 6.3.4.5 Cluster Management with SLOs 168 -- 6.4 Reconfigurations in NoSQL and Key-Value Storage/Databases 169 -- 6.4.1 Motivation 169 -- 6.4.2 Morphus: Reconfigurations in Sharded Databases/Storage 170 -- 6.4.2.1 Assumptions 170 -- 6.4.2.2 MongoDB System Model 170 -- 6.4.2.3 Reconfiguration Phases in Morphus 171 -- 6.4.2.4 Algorithms for Efficient Shard Key Reconfigurations 172 -- 6.4.2.5 Network Awareness 175 -- 6.4.2.6 Evaluation 175 -- 6.4.3 Parqua: Reconfigurations in Distributed Key-Value Stores 179 -- 6.4.3.1 System Model 180 -- 6.4.3.2 System Design and Implementation 181 -- 6.4.3.3 Experimental Evaluation 183 -- 6.5 Scale-Out and Scale-In Operations 185 -- 6.5.1 Stela: Scale-Out/Scale-In in Distributed Stream Processing Systems 186 -- 6.5.1.1 Motivation 186 -- 6.5.1.2 Data Stream Processing Model and Assumptions 187 -- 6.5.1.3 Stela: Scale-Out Overview 187 -- 6.5.1.4 Effective Throughput Percentage (ETP) 188 -- 6.5.1.5 Iterative Assignment and Intuition 190 -- 6.5.1.6 Stela: Scale-In 191 -- 6.5.1.7 Core Architecture 191 -- 6.5.1.8 Evaluation 193 -- 6.5.1.9 Experimental Setup 193 -- 6.5.1.10 Yahoo! Storm Topologies and Network Monitoring Topology 193 -- 6.5.1.11 Convergence Time 195 -- 6.5.1.12 Scale-In Experiments 196 -- 6.5.2 Scale-Out/Scale-In in Distributed Graph Processing Systems 197 -- 6.5.2.1 Motivation 197 -- 6.5.2.2 What to Migrate, and How? 199 -- 6.5.2.3 When to Migrate? 201 -- 6.5.2.4 Evaluation 203 -- 6.6 Priorities and Deadlines in Batch Processing Systems 204 -- 6.6.1 Natjam: Supporting Priorities and Deadlines in Hadoop 204 -- 6.6.1.1 Motivation 204 -- 6.6.1.2 Eviction Policies for a Dual-Priority Setting 206 -- 6.6.1.3 Natjam Architecture 209.
6.6.1.4 Natjam-R: Deadline-Based Eviction 215 -- 6.6.1.5 Microbenchmarks 216 -- 6.6.1.6 Natjam-R Evaluation 221 -- 6.7 Summary 223 -- 6.8 The Future 224 -- 7 Theoretical Considerations: Inferring and Enforcing Use Patterns for Mobile Cloud Assurance 237 /Gul Agha, Minas Charalambides, Kirill Mechitov, Karl Palmskog,Atul Sandur, and Reza Shiftehfar -- 7.1 Introduction 237 -- 7.2 Vision 239 -- 7.3 State of the Art 240 -- 7.3.1 Code Offloading 241 -- 7.3.2 Coordination Constraints 241 -- 7.3.3 Session Types 242 -- 7.4 Code Offloading and the IMCM Framework 243 -- 7.4.1 IMCM Framework: Overview 244 -- 7.4.2 Cloud Application and Infrastructure Models 244 -- 7.4.3 Cloud Application Model 245 -- 7.4.4 Defining Privacy for Mobile Hybrid Cloud Applications 247 -- 7.4.5 A Face Recognition Application 247 -- 7.4.6 The Design of an Authorization System 249 -- 7.4.7 Mobile Hybrid Cloud Authorization Language 250 -- 7.4.7.1 Grouping, Selection, and Binding 252 -- 7.4.7.2 Policy Description 252 -- 7.4.7.3 Policy Evaluation 253 -- 7.4.8 Performance- and Energy-Usage-Based Code Offloading 254 -- 7.4.8.1 Offloading for Sequential Execution on a Single Server 254 -- 7.4.8.2 Offloading for Parallel Execution on Hybrid Clouds 255 -- 7.4.8.3 Maximizing Performance 255 -- 7.4.8.4 Minimizing Energy Consumption 256 -- 7.4.8.5 Energy Monitoring 257 -- 7.4.8.6 Security Policies and Energy Monitoring 258 -- 7.5 Coordinating Actors 259 -- 7.5.1 Expressing Coordination 259 -- 7.5.1.1 Synchronizers 260 -- 7.5.1.2 Security Issues in Synchronizers 260 -- 7.6 Session Types 264 -- 7.6.1 Session Types for Actors 265 -- 7.6.1.1 Example: Sliding Window Protocol 265 -- 7.6.2 Global Types 266 -- 7.6.3 Programming Language 268 -- 7.6.4 Local Types and Type Checking 269 -- 7.6.5 Realization of Global Types 270 -- 7.7 The Future 271 -- Acknowledgments 272 -- 8 Certifications Past and Future: A Future Model for Assigning Certifications that Incorporate Lessons Learned from Past Practices 277 /Masooda Bashir, Carlo Di Giulio, and Charles A. Kamhoua.
8.1 Introduction 277 -- 8.1.1 What Is a Standard? 279 -- 8.1.2 Standards and Cloud Computing 281 -- 8.2 Vision: Using Cloud Technology in Missions 283 -- 8.3 State of the Art 284 -- 8.3.1 The Federal Risk Authorization Management Program 286 -- 8.3.2 SOC Reports and TSPC 288 -- 8.3.3 ISO/IEC 27001 291 -- 8.3.4 Main Differences among the Standards 292 -- 8.3.5 Other Existing Frameworks 293 -- 8.3.5.1 PCI-DSS 293 -- 8.3.5.2 C5 294 -- 8.3.5.3 STAR 294 -- 8.3.6 What Protections Do Standards Offer against Vulnerabilities in the Cloud? 294 -- 8.4 Comparison among Standards 296 -- 8.4.1 Strategy for Comparing Standards 298 -- 8.4.2 Patterns, Anomalies, and Discoveries 299 -- 8.5 The Future 302 -- 8.5.1 Current Challenges 304 -- 8.5.2 Opportunities 305 -- 9 Summary and Future Work 312 /Roy H. Campbell -- 9.1 Survivability 312 -- 9.2 Risks and Benefits 313 -- 9.3 Detection and Security 314 -- 9.4 Scalability, Workloads, and Performance 316 -- 9.5 Resource Management 319 -- 9.6 Theoretical Considerations: Inferring and Enforcing Use Patterns for Mobile Cloud Assurance 321 -- 9.7 Certifications 322 -- Index 327.
Record Nr. UNINA-9910555182003321
Campbell Roy  
Hoboken, New Jersey : , : IEEE Computer Society, Inc./Wiley, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Assured cloud computing / / edited by Roy H. Campbell, Charles A. Kamhoua, Kevin A. Kwiat
Assured cloud computing / / edited by Roy H. Campbell, Charles A. Kamhoua, Kevin A. Kwiat
Autore Campbell Roy
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, New Jersey : , : IEEE Computer Society, Inc./Wiley, , 2018
Descrizione fisica 1 online resource (363 pages)
Disciplina 004.67/82
Soggetto topico Cloud computing
ISBN 1-119-42850-5
1-119-42848-3
1-119-42849-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xiii -- Editors’ Biographies xvii -- List of Contributors xix -- 1 Introduction 1 /Roy H. Campbell -- 1.1 Introduction 1 -- 1.1.1 Mission-Critical Cloud Solutions for the Military 2 -- 1.2 Overview of the Book 3 -- 2 Survivability: Design, Formal Modeling, and Validation of Cloud Storage Systems Using Maude 10 /Rakesh Bobba, Jon Grov, Indranil Gupta, Si Liu, José Meseguer,Peter Csaba Ölveczky, and Stephen Skeirik -- 2.1 Introduction 10 -- 2.1.1 State of the Art 11 -- 2.1.2 Vision: Formal Methods for Cloud Storage Systems 12 -- 2.1.3 The Rewriting Logic Framework 13 -- 2.1.4 Summary: Using Formal Methods on Cloud Storage Systems 15 -- 2.2 Apache Cassandra 17 -- 2.3 Formalizing, Analyzing, and Extending Google’s Megastore 23 -- 2.3.1 Specifying Megastore 23 -- 2.3.2 Analyzing Megastore 25 -- 2.3.2.1 Megastore-CGC 29 -- 2.4 RAMP Transaction Systems 30 -- 2.5 Group Key Management via ZooKeeper 31 -- 2.5.1 ZooKeeper Background 32 -- 2.5.2 System Design 33 -- 2.5.3 Maude Model 34 -- 2.5.4 Analysis and Discussion 35 -- 2.6 How Amazon Web Services Uses Formal Methods 37 -- 2.6.1 Use of Formal Methods 37 -- 2.6.2 Outcomes and Experiences 38 -- 2.6.3 Limitations 39 -- 2.7 Related Work 40 -- 2.8 Concluding Remarks 42 -- 2.8.1 The Future 43 -- 3 Risks and Benefits: Game-Theoretical Analysis and Algorithm for Virtual Machine Security Management in the Cloud 49 /Luke Kwiat, Charles A. Kamhoua, Kevin A. Kwiat, and Jian Tang -- 3.1 Introduction 49 -- 3.2 Vision: Using Cloud Technology in Missions 51 -- 3.3 State of the Art 54 -- 3.4 System Model 57 -- 3.5 Game Model 59 -- 3.6 Game Analysis 61 -- 3.7 Model Extension and Discussion 67 -- 3.8 Numerical Results and Analysis 71 -- 3.8.1 Changes in User 2’s Payoff with Respect to L2 71 -- 3.8.2 Changes in User 2’s Payoff with Respect to e 72 -- 3.8.3 Changes in User 2’s Payoff with Respect to π 73 -- 3.8.4 Changes in User 2’s Payoff with Respect to qI 74 -- 3.8.5 Model Extension to n = 10 Users 75.
3.9 The Future 78 -- 4 Detection and Security: Achieving Resiliency by Dynamic and Passive System Monitoring and Smart Access Control 81 /Zbigniew Kalbarczyk -- 4.1 Introduction 82 -- 4.2 Vision: Using Cloud Technology in Missions 83 -- 4.3 State of the Art 84 -- 4.4 Dynamic VM Monitoring Using Hypervisor Probes 85 -- 4.4.1 Design 86 -- 4.4.2 Prototype Implementation 88 -- 4.4.3 Example Detectors 90 -- 4.4.3.1 Emergency Exploit Detector 90 -- 4.4.3.2 Application Heartbeat Detector 91 -- 4.4.4 Performance 93 -- 4.4.4.1 Microbenchmarks 93 -- 4.4.4.2 Detector Performance 94 -- 4.4.5 Summary 95 -- 4.5 Hypervisor Introspection: A Technique for Evading Passive Virtual Machine Monitoring 96 -- 4.5.1 Hypervisor Introspection 97 -- 4.5.1.1 VMI Monitor 97 -- 4.5.1.2 VM Suspend Side-Channel 97 -- 4.5.1.3 Limitations of Hypervisor Introspection 98 -- 4.5.2 Evading VMI with Hypervisor Introspection 98 -- 4.5.2.1 Insider Attack Model and Assumptions 98 -- 4.5.2.2 Large File Transfer 99 -- 4.5.3 Defenses against Hypervisor Introspection 101 -- 4.5.3.1 Introducing Noise to VM Clocks 101 -- 4.5.3.2 Scheduler-Based Defenses 101 -- 4.5.3.3 Randomized Monitoring Interval 102 -- 4.5.4 Summary 103 -- 4.6 Identifying Compromised Users in Shared Computing Infrastructures 103 -- 4.6.1 Target System and Security Data 104 -- 4.6.1.1 Data and Alerts 105 -- 4.6.1.2 Automating the Analysis of Alerts 106 -- 4.6.2 Overview of the Data 107 -- 4.6.3 Approach 109 -- 4.6.3.1 The Model: Bayesian Network 109 -- 4.6.3.2 Training of the Bayesian Network 110 -- 4.6.4 Analysis of the Incidents 112 -- 4.6.4.1 Sample Incident 112 -- 4.6.4.2 Discussion 113 -- 4.6.5 Supporting Decisions with the Bayesian Network Approach 114 -- 4.6.5.1 Analysis of the Incidents 114 -- 4.6.5.2 Analysis of the Borderline Cases 116 -- 4.6.6 Conclusion 118 -- 4.7 Integrating Attribute-Based Policies into Role-Based Access Control 118 -- 4.7.1 Framework Description 119 -- 4.7.2 Aboveground Level: Tables 119 -- 4.7.2.1 Environment 120.
4.7.2.2 User-Role Assignments 120 -- 4.7.2.3 Role-Permission Assignments 121 -- 4.7.3 Underground Level: Policies 121 -- 4.7.3.1 Role-Permission Assignment Policy 122 -- 4.7.3.2 User-Role Assignment Policy 123 -- 4.7.4 Case Study: Large-Scale ICS 123 -- 4.7.4.1 RBAC Model-Building Process 124 -- 4.7.4.2 Discussion of Case Study 127 -- 4.7.5 Concluding Remarks 128 -- 4.8 The Future 128 -- 5 Scalability, Workloads, and Performance: Replication, Popularity, Modeling, and Geo-Distributed File Stores 133 /Roy H. Campbell, Shadi A. Noghabi, and Cristina L. Abad -- 5.1 Introduction 133 -- 5.2 Vision: Using Cloud Technology in Missions 134 -- 5.3 State of the Art 136 -- 5.4 Data Replication in a Cloud File System 137 -- 5.4.1 MapReduce Clusters 138 -- 5.4.1.1 File Popularity, Temporal Locality, and Arrival Patterns 142 -- 5.4.1.2 Synthetic Workloads for Big Data 144 -- 5.4.2 Related Work 147 -- 5.4.3 Contribution from Our Approach to Generating Big Data Request Streams Using Clustered Renewal Processes 149 -- 5.4.3.1 Scalable Geo-Distributed Storage 149 -- 5.4.4 Related Work 151 -- 5.4.5 Summary of Ambry 152 -- 5.5 Summary 153 -- 5.6 The Future 153 -- 6 Resource Management: Performance Assuredness in Distributed Cloud Computing via Online Reconfigurations 160 /Mainak Ghosh, Le Xu, and Indranil Gupta -- 6.1 Introduction 161 -- 6.2 Vision: Using Cloud Technology in Missions 163 -- 6.3 State of the Art 164 -- 6.3.1 State of the Art: Reconfigurations in Sharded Databases/Storage 164 -- 6.3.1.1 Database Reconfigurations 164 -- 6.3.1.2 Live Migration 164 -- 6.3.1.3 Network Flow Scheduling 164 -- 6.3.2 State of the Art: Scale-Out/Scale-In in Distributed Stream Processing Systems 165 -- 6.3.2.1 Real-Time Reconfigurations 165 -- 6.3.2.2 Live Migration 165 -- 6.3.2.3 Real-Time Elasticity 165 -- 6.3.3 State of the Art: Scale-Out/Scale-In in Distributed Graph Processing Systems 166 -- 6.3.3.1 Data Centers 166 -- 6.3.3.2 Cloud and Storage Systems 166 -- 6.3.3.3 Data Processing Frameworks 166.
6.3.3.4 Partitioning in Graph Processing 166 -- 6.3.3.5 Dynamic Repartitioning in Graph Processing 167 -- 6.3.4 State of the Art: Priorities and Deadlines in Batch Processing Systems 167 -- 6.3.4.1 OS Mechanisms 167 -- 6.3.4.2 Preemption 167 -- 6.3.4.3 Real-Time Scheduling 168 -- 6.3.4.4 Fairness 168 -- 6.3.4.5 Cluster Management with SLOs 168 -- 6.4 Reconfigurations in NoSQL and Key-Value Storage/Databases 169 -- 6.4.1 Motivation 169 -- 6.4.2 Morphus: Reconfigurations in Sharded Databases/Storage 170 -- 6.4.2.1 Assumptions 170 -- 6.4.2.2 MongoDB System Model 170 -- 6.4.2.3 Reconfiguration Phases in Morphus 171 -- 6.4.2.4 Algorithms for Efficient Shard Key Reconfigurations 172 -- 6.4.2.5 Network Awareness 175 -- 6.4.2.6 Evaluation 175 -- 6.4.3 Parqua: Reconfigurations in Distributed Key-Value Stores 179 -- 6.4.3.1 System Model 180 -- 6.4.3.2 System Design and Implementation 181 -- 6.4.3.3 Experimental Evaluation 183 -- 6.5 Scale-Out and Scale-In Operations 185 -- 6.5.1 Stela: Scale-Out/Scale-In in Distributed Stream Processing Systems 186 -- 6.5.1.1 Motivation 186 -- 6.5.1.2 Data Stream Processing Model and Assumptions 187 -- 6.5.1.3 Stela: Scale-Out Overview 187 -- 6.5.1.4 Effective Throughput Percentage (ETP) 188 -- 6.5.1.5 Iterative Assignment and Intuition 190 -- 6.5.1.6 Stela: Scale-In 191 -- 6.5.1.7 Core Architecture 191 -- 6.5.1.8 Evaluation 193 -- 6.5.1.9 Experimental Setup 193 -- 6.5.1.10 Yahoo! Storm Topologies and Network Monitoring Topology 193 -- 6.5.1.11 Convergence Time 195 -- 6.5.1.12 Scale-In Experiments 196 -- 6.5.2 Scale-Out/Scale-In in Distributed Graph Processing Systems 197 -- 6.5.2.1 Motivation 197 -- 6.5.2.2 What to Migrate, and How? 199 -- 6.5.2.3 When to Migrate? 201 -- 6.5.2.4 Evaluation 203 -- 6.6 Priorities and Deadlines in Batch Processing Systems 204 -- 6.6.1 Natjam: Supporting Priorities and Deadlines in Hadoop 204 -- 6.6.1.1 Motivation 204 -- 6.6.1.2 Eviction Policies for a Dual-Priority Setting 206 -- 6.6.1.3 Natjam Architecture 209.
6.6.1.4 Natjam-R: Deadline-Based Eviction 215 -- 6.6.1.5 Microbenchmarks 216 -- 6.6.1.6 Natjam-R Evaluation 221 -- 6.7 Summary 223 -- 6.8 The Future 224 -- 7 Theoretical Considerations: Inferring and Enforcing Use Patterns for Mobile Cloud Assurance 237 /Gul Agha, Minas Charalambides, Kirill Mechitov, Karl Palmskog,Atul Sandur, and Reza Shiftehfar -- 7.1 Introduction 237 -- 7.2 Vision 239 -- 7.3 State of the Art 240 -- 7.3.1 Code Offloading 241 -- 7.3.2 Coordination Constraints 241 -- 7.3.3 Session Types 242 -- 7.4 Code Offloading and the IMCM Framework 243 -- 7.4.1 IMCM Framework: Overview 244 -- 7.4.2 Cloud Application and Infrastructure Models 244 -- 7.4.3 Cloud Application Model 245 -- 7.4.4 Defining Privacy for Mobile Hybrid Cloud Applications 247 -- 7.4.5 A Face Recognition Application 247 -- 7.4.6 The Design of an Authorization System 249 -- 7.4.7 Mobile Hybrid Cloud Authorization Language 250 -- 7.4.7.1 Grouping, Selection, and Binding 252 -- 7.4.7.2 Policy Description 252 -- 7.4.7.3 Policy Evaluation 253 -- 7.4.8 Performance- and Energy-Usage-Based Code Offloading 254 -- 7.4.8.1 Offloading for Sequential Execution on a Single Server 254 -- 7.4.8.2 Offloading for Parallel Execution on Hybrid Clouds 255 -- 7.4.8.3 Maximizing Performance 255 -- 7.4.8.4 Minimizing Energy Consumption 256 -- 7.4.8.5 Energy Monitoring 257 -- 7.4.8.6 Security Policies and Energy Monitoring 258 -- 7.5 Coordinating Actors 259 -- 7.5.1 Expressing Coordination 259 -- 7.5.1.1 Synchronizers 260 -- 7.5.1.2 Security Issues in Synchronizers 260 -- 7.6 Session Types 264 -- 7.6.1 Session Types for Actors 265 -- 7.6.1.1 Example: Sliding Window Protocol 265 -- 7.6.2 Global Types 266 -- 7.6.3 Programming Language 268 -- 7.6.4 Local Types and Type Checking 269 -- 7.6.5 Realization of Global Types 270 -- 7.7 The Future 271 -- Acknowledgments 272 -- 8 Certifications Past and Future: A Future Model for Assigning Certifications that Incorporate Lessons Learned from Past Practices 277 /Masooda Bashir, Carlo Di Giulio, and Charles A. Kamhoua.
8.1 Introduction 277 -- 8.1.1 What Is a Standard? 279 -- 8.1.2 Standards and Cloud Computing 281 -- 8.2 Vision: Using Cloud Technology in Missions 283 -- 8.3 State of the Art 284 -- 8.3.1 The Federal Risk Authorization Management Program 286 -- 8.3.2 SOC Reports and TSPC 288 -- 8.3.3 ISO/IEC 27001 291 -- 8.3.4 Main Differences among the Standards 292 -- 8.3.5 Other Existing Frameworks 293 -- 8.3.5.1 PCI-DSS 293 -- 8.3.5.2 C5 294 -- 8.3.5.3 STAR 294 -- 8.3.6 What Protections Do Standards Offer against Vulnerabilities in the Cloud? 294 -- 8.4 Comparison among Standards 296 -- 8.4.1 Strategy for Comparing Standards 298 -- 8.4.2 Patterns, Anomalies, and Discoveries 299 -- 8.5 The Future 302 -- 8.5.1 Current Challenges 304 -- 8.5.2 Opportunities 305 -- 9 Summary and Future Work 312 /Roy H. Campbell -- 9.1 Survivability 312 -- 9.2 Risks and Benefits 313 -- 9.3 Detection and Security 314 -- 9.4 Scalability, Workloads, and Performance 316 -- 9.5 Resource Management 319 -- 9.6 Theoretical Considerations: Inferring and Enforcing Use Patterns for Mobile Cloud Assurance 321 -- 9.7 Certifications 322 -- Index 327.
Record Nr. UNINA-9910830412903321
Campbell Roy  
Hoboken, New Jersey : , : IEEE Computer Society, Inc./Wiley, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Automation through Chef Opscode : A Hands-on Approach to Chef / / by Navin Sabharwal, Manak Wadhwa
Automation through Chef Opscode : A Hands-on Approach to Chef / / by Navin Sabharwal, Manak Wadhwa
Autore Sabharwal Navin
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Berkeley, CA : , : Apress : , : Imprint : Apress, , 2014
Descrizione fisica 1 online resource (255 p.)
Disciplina 004.67/82
Collana The expert's voice in information technology
Soggetto topico Open source software
Computer programming
Software engineering
Open Source
Software Engineering/Programming and Operating Systems
ISBN 9781430262961
1430262966
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910300465003321
Sabharwal Navin  
Berkeley, CA : , : Apress : , : Imprint : Apress, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Azure Arc Systems Management : Governance and Administration of Multi-cloud and Hybrid IT Estates / / by Ramona Maxwell
Azure Arc Systems Management : Governance and Administration of Multi-cloud and Hybrid IT Estates / / by Ramona Maxwell
Autore Maxwell Ramona
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Berkeley, CA : , : Apress : , : Imprint : Apress, , 2024
Descrizione fisica 1 online resource (298 pages)
Disciplina 004.67/82
Soggetto topico Microsoft software
Microsoft .NET Framework
Cloud computing
Database management
Microsoft
Cloud Computing
Database Management
ISBN 9781484294802
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. The Challenges of Enterprise-scale Hybrid and Multi-cloud Architectures -- Chapter 2. What Is Azure Arc? -- Chapter 3. Overview of the Benefits of Arc in the Enterprise -- Chapter 4. Securing the Enterprise with Arc -- Chapter 5. Enterprise DBS Management and Arc -- Chapter 6. Managing Kubernetes Workloads in Hybrid or Multi-cloud Datacenters -- Chapter 7. Policy and Governance Across Hybrid and Multi-cloud Infrastructure -- Chapter 8. Process Automation via the Arc Control Plane -- Chapter 9. Automation in the Era of ML and AI -- Chapter 10. Azure Arc – History and Horizons.
Record Nr. UNINA-9910855394703321
Maxwell Ramona  
Berkeley, CA : , : Apress : , : Imprint : Apress, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
The basics of cloud computing : understanding the fundamentals of cloud computing in theory and practice / / Derrick Rountree, Ileana Castrillo ; Hai Jiang, technical editor
The basics of cloud computing : understanding the fundamentals of cloud computing in theory and practice / / Derrick Rountree, Ileana Castrillo ; Hai Jiang, technical editor
Autore Rountree Derrick
Edizione [1st edition]
Pubbl/distr/stampa Amsterdam : , : Syngress, an imprint of Elsevier, , [2014]
Descrizione fisica 1 online resource (174 p.)
Disciplina 004.67/82
Altri autori (Persone) CastrilloIleana
JiangHai
Collana The basics The basics of cloud computing
Soggetto topico Cloud computing
Soggetto genere / forma Electronic books.
ISBN 0-12-405521-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction to the Cloud -- Laying the Ground Work -- Cloud Deployment Models -- Cloud Service Models -- Making the Decision -- Evaluating Cloud Security -- Operating a Cloud.
Record Nr. UNINA-9910453126003321
Rountree Derrick  
Amsterdam : , : Syngress, an imprint of Elsevier, , [2014]
Materiale a stampa
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