| 000 | 03262nam a22004215i 4500 | ||
|---|---|---|---|
| 999 |
_c395791 _d395791 |
||
| 001 | 395791 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230123230332.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230123s2022 sz | s |1|| 0|eng d | ||
| 020 | _a9783030922313 | ||
| 024 | 7 |
_a10.1007/978-3-030-92231-3 _2doi |
|
| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
||
| 050 | 4 |
_aTK5105.888 _b2022 EB |
|
| 245 | 0 | 0 |
_aICWE 2021 Workshops : _bICWE 2021 International Workshops, BECS and Invited Papers, Biarritz, France, May 18-21, 2021, Revised Selected Papers _cedited by Maxim Bakaev, In-Young Ko, Michael Mrissa, Cesare Pautasso, Abhishek Srivastava |
| 250 | _a1st edition 2022 | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2022 |
|
| 300 |
_a1 recurso en línea (XI, 99 páginas) _b32 ilustraciones, 30 ilustraciones a color |
||
| 336 |
_atexto _btxt _2rdacontent |
||
| 337 |
_aelectrónico _bc _2rdamedia |
||
| 338 |
_arecurso electrónico _bcr _2rdacarrier |
||
| 347 |
_aarchivo de texto _bPDF |
||
| 490 | 0 |
_aCommunications in Computer and Information Science _x1865-0937 _v1508 |
|
| 505 | 0 | _aBECS 2021 -- Putting Data Science Pipelines on the Edge -- DNN Model Deployment on Distributed Edges -- Towards Proactive Context-Aware IoT Environments by means of Federated Learning -- Real-time Deep Learning-based Anomaly Detection Approach for Multivariate Data Streams with Apache Flink -- A Novel Approach to Dynamic Pricing for Cloud Computing Through Price Band Prediction -- Learning-based Activation of Energy Harvesting Sensors for Fresh Data Acquisition -- Invited Papers -- Exploiting Triangle Patterns for Heterogeneous Graph Attention Network -- Towards Seamless IoT Device-Edge-Cloud Continuum: Software Architecture Options of IoT Devices Revisited. | |
| 520 | _aThis book constitutes the thoroughly refereed post-workshop proceedings of the 21th International Conference on Web Engineering, ICWE 2021, held in Biarritz, France, in May 2021.* The first international workshop on Big data-driven Edge Cloud Services (BECS 2021) was held to provide a venue in which scholars and practitioners can share their experiences and present on-going work on providing value-added Web services for users by utilizing big data in edge cloud environments. The 5 revised full papers and 1 revised short contribution selected from 11 submissions are presented with 2 invited papers. *The conference was held virtually due to the COVID-19 pandemic. | ||
| 988 | _aSpringer_Computer_2022 | ||
| 650 | 7 |
_2embne _9405542 _aWorld Wide Web (Sistema de recuperación de la información) _vCongresos y asamblas |
|
| 650 | 7 |
_2embne _9152630 _aIngeniería del software _vCongresos y asamblas |
|
| 650 | 7 |
_2embne _9162329 _aServicios Web _vCongresos y asamblas |
|
| 776 | 0 | 8 |
_iPrinted edition: _z9783030922306 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030922320 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi-org.ezproxy.universidadeuropea.es/10.1007/978-3-030-92231-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
||
| 998 |
_b01/2023 _dz _eIG _zSI |
||