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ES-MaUEC |
| 005 - FECHA Y HORA DE LA ÚLTIMA TRANSACCIÓN |
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| 020 ## - NÚMERO INTERNACIONAL ESTÁNDAR DEL LIBRO |
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| Número Internacional Estándar del Libro |
9783031339202 |
| 024 7# - IDENTIFICADOR DE OTROS ESTÁNDARES |
|---|
| Número estándar o código |
10.1007/978-3-031-33920-2 |
| Fuente del número o código |
doi |
| 040 ## - FUENTE DE LA CATALOGACIÓN |
|---|
| Centro catalogador/agencia de origen |
ES-MaUEC |
| Lengua de catalogación |
spa |
| Centro/agencia transcriptor |
ES-MaUEC |
| Centro/agencia modificador |
ES-MaUEC |
| 050 #4 - SIGNATURA TOPOGRÁFICA DE LA BIBLIOTECA DEL CONGRESO |
|---|
| Número de clasificación |
QA76.585 |
| Número de documento/Ítem |
2023 EB |
| 100 1# - ENTRADA PRINCIPAL--NOMBRE DE PERSONA |
|---|
| Nombre de persona |
Tran-Dang, Hoa |
| Término indicativo de función/relación |
autor |
| Código de función/relación |
http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) |
689616 |
| 245 10 - MENCIÓN DE TÍTULO |
|---|
| Título |
Cooperative and Distributed Intelligent Computation in Fog Computing : |
| Resto del título |
Concepts, Architectures, and Frameworks |
| Mención de responsabilidad, etc. |
by Hoa Tran-Dang, Dong-Seong Kim |
| 250 ## - MENCIÓN DE EDICIÓN |
|---|
| Mención de edición |
1st ed 2023 |
| 264 #1 - PRODUCCIÓN, PUBLICACIÓN, DISTRIBUCIÓN, FABRICACIÓN Y COPYRIGHT |
|---|
| Producción, publicación, distribución, fabricación y copyright |
Cham |
| Nombre del de productor, editor, distribuidor, fabricante |
Springer Nature Switzerland |
| Fecha de producción, publicación, distribución, fabricación o copyright |
2023 |
| 300 ## - DESCRIPCIÓN FÍSICA |
|---|
| Extensión |
1 recurso en línea |
| 336 ## - TIPO DE CONTENIDO |
|---|
| Término de tipo de contenido |
texto |
| Código de tipo de contenido |
txt |
| Fuente |
rdacontent |
| 337 ## - TIPO DE MEDIO |
|---|
| Nombre/término del tipo de medio |
electrónico |
| Código del tipo de medio |
c |
| Fuente |
rdamedia |
| 338 ## - TIPO DE SOPORTE |
|---|
| Nombre/término del tipo de soporte |
recurso electrónico |
| Código del tipo de soporte |
cr |
| Fuente |
rdacarrier |
| 347 ## - CARACTERÍSTICAS DEL ARCHIVO DIGITAL |
|---|
| Tipo de archivo |
text file |
| Formato de codificación |
PDF |
| Fuente |
rda |
| 505 0# - NOTA DE CONTENIDO CON FORMATO |
|---|
| Nota de contenido con formato |
Fog Computing: Concepts & Recent Advances -- 1.1 Introduction -- 1.2 Fog Computing Architectures -- 1.2.1 Hierarchical Architecture Model -- 1.2.2 Layered Architecture Model -- 1.3 Computation Offloading in Fog Computing Architectures -- 1.4 Key Technologies for Future Fog Computing Architectures -- 1.4.1 Communication and Networking Technologies -- 1.4.2 Virtualization Technologies -- 1.4.3 Storage Technologies -- 1.4.4 Privacy and Data Security Technologies -- 1.5 Conclusions -- 2 Applications of Fog Computing -- 2.1 Introduction -- 2.2 Typical Applications of Fog Computing -- 2.2.1 Healthcare -- 2.2.2 Smart Cities -- 2.2.3 Smart Grid -- 2.2.4 Industrial Robotics and Automation in Smart Factories -- 2.2.5 Agriculture -- 2.2.6 Logistics and Supply Chains -- 2.3 Summary and Conclusions -- -- 3 Cooperation for Distributed Task Offloading in Fog Computing Networks -- 3.1 Introduction -- 3.2 System Model -- 3.2.1 Fog Computing Networks -- 3.2.2 Computation Tasks -- 3.2.3 Computation Offloading Model -- 3.3 Cooperation-based Task Offloading Models -- 3.4 Open Research Issues -- 3.4.1 Data Fragmentation -- 3.4.2 Distribution of Fog Networks -- 3.4.3 Advances of Distributed Algorithms -- 3.4.4 Comprehensive Performance Analysis -- 3.5 Conclusions -- -- 4 Fog Resource Aware Framework for Adaptive Task Offloading in Fog-based IoT Systems -- 4.1 Introduction -- 4.2 Related Works -- 4.3 System Model and Problem Formulation -- 4.3.1 System Model -- 4.3.2 Problem Formulation 4.4 FRATO: Fog Resource Aware Task Offloading Framework -- 4.4.1 Offloading Strategies for Minimizing Service Provisioning Delay -- 4.4.2 Mathematical Formulation of FRATO -- 4.4.3 Solution Deployment Analysis -- 4.5 Distributed Resource Allocation in Fog -- 4.5.1 Task Priority-based Resource Allocation -- 4.5.2 Maximal Resource Utilization based Allocation -- 4.6 Simulation and Performance Evaluation -- 4.6.1 Simulation Environment Setup -- 4.6.2 Comparative Approaches -- 4.6.3 Evaluation and Analysis -- 4.6.4 Further Analysis of Computation Time and Complexity -- 4.7 Conclusions -- 4.8 Future Works -- 4.8.1 Data Fragmentation -- 4.8.2 Distribution of Fog Networks -- 4.8.3 Advance of Optimization Algorithms -- 4.8.4 Comprehensive Performance Analysis -- -- 5 Dynamic Collaborative Task Offloading in Fog computing Systems -- 5.1 Introduction -- 5.2 Related Works -- 5.3 System Model and Problem Formulation -- 5.3.1 System Model -- 5.3.2 Computation Task Model -- 5.3.3 Problem Formulation -- 5.4 Optimization Problem for Minimization of Task Execution Delay -- 5.5 Simulation and Performance Evaluation -- 5.5.1 Simulation Environment Setup -- 5.5.2 Evaluation and Analysis -- 5.6 Conclusions and Future Works -- 6 Fundamentals of Matching Theory -- 6.1 Introduction -- 6.2 Basic Concepts and Terminologies -- 6.3 Classification -- 6.3.1 One-to-One (OTO) Matching -- 6.3.2 Many-to-One (MTO) Matching -- 6.3.3 Many-to-Many (MTM) Matching -- 6.3.4 Variants of Matching Models -- 6.4 Matching Algorithms -- 6.5 Conclusions -- 7 Matching Theory for Distributed Computation Offloading in Fog Computing Systems -- 7.1 Introduction -- 7.2 System and Offloading Problem Description -- 7.2.1 System Model -- 7.2.2 Computation Tasks -- 7.2.3 Computation Offloading Models -- 7.2.4 Optimization Problems of Computational Offloading -- 7.3 Proposed Matching-based Models for Distributed Computation -- 7.3.1 One-to-One (OTO) Matching -- 7.3.2 Many-to-One (MTO) Matching7 -- 7.3.3 Many-to-Many (MTM) Matching -- 7.4 Challenges and Open Research Issues -- 7.4.1 Matching With Dynamics -- 7.4.2 Matching with Groups -- 7.4.3 Matching with Externality -- 7.4.4 Security and Privacy of Data and End Users -- 7.4.5 New Offloading Application Scenarios -- 7.4.6 Application of AI and ML-Based Techniques -- 7.5 Conclusions -- 8 Distributed Computation Offloading Frameworks for Fog Networks -- 8.1 Introduction -- 8.2 Preliminary and Related Works -- 8.2.1 Preliminary of Many-to-One (M2O) Matching Model -- 8.2.2 Related Works -- 8.3 System Model -- 8.3.1 Fog Computing Networks -- 8.3.2 Computation Offloading Model -- 8.4 Problem Formulation -- 8.5 Description of DISCO Framework -- 8.5.1 Overview -- 8.5.2 PL Construction -- 8.5.3 Matching Algorithms -- 8.5.4 Optimal Task Offloading and Communication Scheduling Algorithm -- 8.5.5 Stability Analysis -- 8.6 Simulations and Performance Evaluation -- 8.6.1 Simulation Environment Setup -- 8.6.2 Evaluation and Analysis -- 8.7 Conclusions -- 9 Reinforcement Learning-based Resource Allocations in Fog Networks -- 9.1 Introduction -- 9.2 Fog Computing Environment -- 9.2.1 System Model -- 9.2.2 Resource Allocation Problems in Fog Computing Systems -- 9.3 Reinforcement Learning -- 9.3.1 Basic Concepts -- 9.3.2 Taxonomy of RL Algorithms -- 9.4 RL based Algorithms for Resource Allocation in FC Systems -- 9.4.1 Resource Sharing and Management -- 9.4.2 Task Scheduling -- 9.4.3 Task Offloading and Redistribution -- 9.5 Challenges and Open Issues of RL-based Resource Allocations -- 9.5.1 RL-related Challenges -- 9.5.2 Fog Computing Environment related Challenges -- 9.5.3 Computation Task related Challenges -- 9.6 Conclusions and Discussions -- -- -- 10 Bandit Learning and Matching based Distributed Task Offloading in Fog Networks -- 10.1 Introduction -- 10.2 Bacground and Related Works -- 10.2.1 One-to-One Matching-based Task Offloading -- 10.2.2 Bandit Learning-based Computation Offloading -- 10.3 System Model -- 10.3.1 Fog Computing networks -- 10.3.2 Computation Offloading Model -- 10.4 Design of BLM-DTO Algorithm -- 10.4.1 OTO Matching Model for Computation Offloading -- 10.4.2 Multi-Player Multi-Armed Bandit with TS -- 10.5 Simulation Results and Evaluation Analysis -- 10.5.1 Simulation Environment Configuration -- 10.5.2 Comparative Evaluation and Analysis -- 10.6 Conclusions and Discussions. |
| 520 ## - SUMARIO, ETC. |
|---|
| Sumario, etc. |
This informative text/reference presents a detailed review of the state of the art in fog computing paradigm. In particular, the book examines a broad range of important cooperative and distributed computation algorithms, along with their design objectives and technical challenges. The coverage includes the conceptual fundamental of fog computing, its practical applications, cooperative and distributed computation algorithms using optimization, swarm intelligence, matching theory, and reinforcement learning methods. Discussions are also provided on remaining challenges and open research issues for designing and developing the efficient distributed computation solutions in the next-generation of fog-enabled IoT systems. |
| 988 ## - NOTA LOCAL 598 |
|---|
| Nota local 598 (boletines) |
Springer_Computer_2023 |
| 650 #7 - PUNTO DE ACCESO ADICIONAL DE MATERIA--TÉRMINO DE MATERIA |
|---|
| Fuente del encabezamiento o término |
embne |
| 9 (RLIN) |
666069 |
| Término de materia o nombre geográfico como elemento de entrada |
Informática en la nube |
| 700 1# - PUNTO DE ACCESO ADICIONAL--NOMBRE DE PERSONA |
|---|
| 9 (RLIN) |
690193 |
| Nombre de persona |
Kim, Dong Seong |
| Término indicativo de función/relación |
autor |
| 856 40 - LOCALIZACIÓN Y ACCESO ELECTRÓNICOS |
|---|
| Identificador Uniforme del Recurso |
https://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-33920-2 |
| Nota pública |
Acceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 ## - ELEMENTOS DE PUNTO DE ACCESO ADICIONAL (KOHA) |
|---|
| Fuente del sistema de clasificación o colocación |
Library of Congress Classification |
| Tipo de ítem Koha |
LIBRO-E NO PRÉSTAMO |
| 998 ## - DATOS ESTADÍSTICOS |
|---|
| Fecha de catalogación |
02/2024 |
| Tipo de materia |
E-book |
| Catalogador |
Irene Bastante |
| Catalogado |
Sí |