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dc.contributor.advisorCadena Carter, Miguel Antoniospa
dc.contributor.authorPinzón Castellanos, Javierspa
dc.date.accessioned2020-06-26T21:35:50Z
dc.date.available2020-06-26T21:35:50Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/20.500.12749/3551
dc.description.abstractDew computing ó la computación de rocío o lágrima ha despertado gran interés en la academia, debido a la separación de los procesos de computación distribuida; donde se encuentran las capas de cloud Computing (computación en la nube), Fog Computing (computación de niebla), Edge Computing (computación de borde) y por último Dew Computing. Estas capas están mencionadas de orden descendente (de mayor a menor) siendo Dew Computing la más cercana al usuario final. Esto se realiza para una mayor comprensión entre las tecnologías y procesos que en ellas se realizan permitiendo su diferenciación. La arquitectura de Internet of Things (IoT) es un paradigma tecnológico que se está formando dentro del ecosistema de computación distribuida, por ende, se requiere resaltar la capa de Dew Computing y su aporte al modelo tecnológico. Es por esto, que se realiza un estado del arte de las arquitecturas Dew Computing e IoT que permitan su comparación con el fin de saber su aporte de forma independiente y en dado caso, cómo podrían integrarse. Se realiza una prueba piloto entre las arquitecturas y una integración de las misma para encontrar los aportes que un modelo del entrega al otro y por último, se plantean posibles escenarios de aplicación que evidencien los beneficios y déficit de la implementación de cada arquitectura en diferentes ámbitos sociales.spa
dc.description.tableofcontentsINTRODUCCIÓN 1. PROBLEMA, PREGUNTA E HIPÓTESIS DE INVESTIGACIÓN 11 2. JUSTIFICACIÓN 11 3. OBJETIVOS DEL PROYECTO 13 3.1 OBJETIVO GENERAL 13 3.2 OBJETIVOS ESPECÍFICOS 13 4. MARCO REFERENCIAL 14 4.1 MARCO CONCEPTUAL 14 4.1.1 Internet of Things 15 4.1.2 Cloud Computing 15 4.1.3 Fog Computing 16 4.1.4 Edge Computing 17 4.1.5 Dew Computing 20 4.2 MARCO TEÓRICO 21 4.3 ESTADO DEL ARTE 22 4.3.1 Revisión sistemática de la literatura 22 4.3.2 Análisis estado del arte 28 4.4 MARCO CONTEXTUAL Y ANTECEDENTES 28 4.5 NORMAS Y ESTÁNDARES 29 4.5.1 Normatividad colombiana 29 4.5.2 Estándares y documentos de referencia 30 4.6 EMPRESAS TECNOLÓGICAS 31 4.6.1 Microsoft Azure IoT Edge 31 4.6.2 Amazon IoT GreenGrass 32 5. DESCRIPCIÓN DEL PROCESO INVESTIGATIVO 34 5.1 ENFOQUE Y TIPO DE INVESTIGACIÓN 34 5.2 FASES Y ACTIVIDADES 34 5.2.1 Elaboración del estado del arte de Dew computing 35 5.2.2 Análisis comparativo entre frameworks para Dew Computing 35 5.2.3 Dispositivo para pruebas 
 36 5.2.4 Pruebas de ambas arquitecturas 40 5.2.5 Análisis de pruebas
 45 6. RESULTADOS 48 6.1 REVISIÓN COMPARATIVA DE DEW COMPUTING E IOT 48 6.2 VENTAJAS Y DESVENTAJAS DE DEW COMPUTING CON IOT. 52 6.2.1 Física 53 6.2.2 Economía 54 6.2.3 Ubicación 54 6.3 OPORTUNIDADES QUE BRINDA DEW COMPUTING 55 6.3.1 Manejo de la energía 55 6.3.2 Procesamiento 55 6.3.3 Almacenamiento 55 6.3.4 Protocolos de comunicación 55 6.3.5 Lenguajes de programación 55 6.3.6 Seguridad de los datos 56 6.3.7 Visualización de los datos 56 7. CONCLUSIONES Y RECOMENDACIONES 57 8. REFERENCIAS 58spa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleAportes de la arquitectura Dew Computing al internet de las cosas: comparaciones entre implementaciones piloto de ambas arquitecturasspa
dc.title.translatedContributions of architecture Dew Computing to the Internet of Things: comparisons between pilot implementations of both architectureseng
dc.degree.nameMagíster en Telemáticaspa
dc.coverageBucaramanga (Colombia)spa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.programMaestría en Telemáticaspa
dc.description.degreelevelMaestríaspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.localTesisspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.subject.keywordsSystems engineeringeng
dc.subject.keywordsTelematicseng
dc.subject.keywordsSoftware engineeringeng
dc.subject.keywordsCloud computingeng
dc.subject.keywordsInvestigationseng
dc.subject.keywordsAnalysiseng
dc.subject.keywordsDew computingeng
dc.subject.keywordsFog computingeng
dc.subject.keywordsInternet of thingseng
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
dc.relation.referencesPinzón Castellanos, Javier (2018). Aportes de la arquitectura dew computing al internet de las cosas. Bucaramanga (Colombia) : Universidad Autónoma de Bucaramanga UNABspa
dc.relation.referencesAWS Developers. (2017, diciembre 12). AWS Greengrass – Computación de Lambda integrada en dispositivos conectados – Amazon Web Services. Recuperado 12 de diciembre de 2017, a partir de //aws.amazon.com/es/greengrass/spa
dc.relation.referencesBrezany, P., Ludescher, T., & Feilhauer, T. (2017). Cloud-Dew computing support for automatic data analysis in life sciences. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 365-370). https://doi.org/10.23919/MIPRO.2017.7973450spa
dc.relation.referencesCabé, B. (2018). Key Trends from the IoT Developer Survey 2018. Recuperado a partir de https://blogs.eclipse.org/post/benjamin-cab%C3%A9/key-trends-iot-developer-survey-2018spa
dc.relation.referencesChang, K.-D., Chen, J.-L., Chen, C.-Y., & Chao, H.-C. (2012). IoT operations management and traffic analysis for Future Internet. En Computing, Communications and Applications Conference (ComComAp), 2012 (pp. 138–142). IEEE.spa
dc.relation.referencesCrnko, N. (2017). Distributed Database System as a base for multilanguage support for legacy software. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 371-374). https://doi.org/10.23919/MIPRO.2017.7973451spa
dc.relation.referencesCrook, S., MacGillivray, C., & Turner, V. (2017, julio 1). IDC MarketScape: Worldwide IoT Platforms (Software Vendors) 2017 Vendor Assessment. Recuperado 12 de diciembre de 2017, a partir de http://www.idc.com/getdoc.jsp?containerId=US42033517spa
dc.relation.referencesDeepti Sharma, P. K. (2015). A Detail Review on Cloud, Fog and Dew Computing. International Journal of Science, Engineering and Technology Research (IJSETR), 5(5), 9.spa
dc.relation.referencesFernández, P. (1996). Determinación del tamaño muestral. Cad Aten Primaria, 3, 138–141.spa
dc.relation.referencesFrincu, M. (2017). Architecting a hybrid cross layer dew-fog-cloud stack for future data-driven cyber-physical systems. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 399-403). https://doi.org/10.23919/MIPRO.2017.7973456spa
dc.relation.referencesGoleva, R. I., Garcia, N. M., Mavromoustakis, C. X., Dobre, C., Mastorakis, G., & Stainov, R. (2017). Chapter 16 - End-Users Testing of Enhanced Living Environment Platform and Services. En Ambient Assisted Living and Enhanced Living Environments (pp. 427-440). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-805195-5.00016-8spa
dc.relation.referencesGoleva, R. I., Garcia, N. M., Mavromoustakis, C. X., Dobre, C., Mastorakis, G., Stainov, R., … Trajkovik, V. (2017). Chapter 8 - AAL and ELE Platform Architecture. En Ambient Assisted Living and Enhanced Living Environments (pp. 171-209). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-805195-5.00008-9spa
dc.relation.referencesGordienko, Y., Stirenko, S., Alienin, O., Skala, K., Sojat, Z., Rojbi, A., … Jervan, G. (2017). Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the basis of Cloud-Fog-Dew computing paradigm. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 359-364). https://doi.org/10.23919/MIPRO.2017.7973449spa
dc.relation.referencesGremban, K., & Street, C. (2017, noviembre 15). What is Azure IoT Edge. Recuperado 7 de diciembre de 2017, a partir de https://docs.microsoft.com/en-us/azure/iot-edge/how-iot-edge-worksspa
dc.relation.referencesGusev, M. (2017). A dew computing solution for IoT streaming devices. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 387-392). https://doi.org/10.23919/MIPRO.2017.7973454spa
dc.relation.referencesGusev, M., & Guseva, A. (2017). State-of-the-art of cloud solutions based on ECG sensors. En IEEE EUROCON 2017 -17th International Conference on Smart Technologies (pp. 501-506). https://doi.org/10.1109/EUROCON.2017.8011162spa
dc.relation.referencesHuang, D., & Wu, H. (2018). Chapter 6 - Edge Clouds – Pushing the Boundary of Mobile Clouds. En Mobile Cloud Computing (pp. 153-176). Morgan Kaufmann. https://doi.org/10.1016/B978-0-12-809641-3.00008-9spa
dc.relation.referencesJóźwiak, L. (2017). Advanced mobile and wearable systems. Microprocessors and Microsystems, 50 (Supplement C), 202-221. https://doi.org/10.1016/j.micpro.2017.03.008spa
dc.relation.referencesKholod, I., Efimova, M., Rukavitsyn, A., & Andrey, S. (2017). Time Series Distributed Analysis in IoT with ETL and Data Mining Technologies. En Internet of Things, Smart Spaces, and Next Generation Networks and Systems (pp. 97-108). Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_9spa
dc.relation.referencesLorga, M., Feldman, L., Barton, R., Martin, M., Goren, N., & Mahmoudi, C. (2017, septiembre 21). The NIST Definition of Fog Computing. Recuperado 11 de octubre de 2017, a partir de https://csrc.nist.gov/publications/detail/sp/800-191/draftspa
dc.relation.referencesLuchian, E. F., Taut, A., Ivanciu, I. A., Lazar, G., & Dobrota, V. (2017). Mobile wireless sensor network gateway: A raspberry Pi implementation with a VPN backend to OpenStack. En 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM) (pp. 1-5). https://doi.org/10.23919/SOFTCOM.2017.8115561spa
dc.relation.referencesMell, P., & Grance, T. (2011, julio 7). The NIST Definition of Cloud Computing. Recuperado 5 de diciembre de 2017, a partir de https://csrc.nist.gov/publications/detail/sp/800-145/finalspa
dc.relation.referencesMSV, J. (2017, septiembre 15). Demystifying Edge Computing -- Device Edge vs. Cloud Edge. Recuperado 12 de octubre de 2017, a partir de https://www.forbes.com/sites/janakirammsv/2017/09/15/demystifying-edge-computing-device-edge-vs-cloud-edge/spa
dc.relation.referencesMulay, P., Patel, K., & Gauchia, H. G. (2017). Distributed system implementation based on «ants feeding birds» algorithm: Electronics transformation via animals and human. En Detecting and Mitigating Robotic Cyber Security Risks (pp. 51-85). https://doi.org/10.4018/978-1-5225-2154-9.ch005spa
dc.relation.referencesPatel, H., Chaudhari, R., R Prajapati, K., & A Patel, A. (2017). The Interdependent Part of Cloud Computing:Dew Computing.spa
dc.relation.referencesPodbojec, D., Herynek, B., Jazbec, D., Cvetko, M., Debevc, M., & Kožuh, I. (2017). 3D-based location positioning using the Dew Computing approach for indoor navigation. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 393-398). https://doi.org/10.23919/MIPRO.2017.7973455spa
dc.relation.referencesQuwaider, M., Al-Alyyoub, M., & Jararweh, Y. (2016). Cloud Support Data Management Infrastructure for Upcoming Smart Cities. Procedia Computer Science, 83, 1232–1237.spa
dc.relation.referencesRay, P. P. (2017). An Introduction to Dew Computing: Definition, Concept and Implications. IEEE Access, PP(99), 1-1. https://doi.org/10.1109/ACCESS.2017.2775042spa
dc.relation.referencesRindos, A., & Wang, Y. (2016). Dew Computing: The Complementary Piece of Cloud Computing. En Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom)(BDCloud-SocialCom-SustainCom), 2016 IEEE International Conferences on (pp. 15–20). IEEE. Recuperado a partir de http://ieeexplore.ieee.org/abstract/document/7723668/spa
dc.relation.referencesRistov, S., Cvetkov, K., & Gusev, M. (2016). Implementation of a Horizontal Scalable Balancer for Dew Computing Services. Scalable Computing: Practice and Experience, 17(2), 79–90.spa
dc.relation.referencesSkala, K., Davidovic, D., Afgan, E., Sovic, I., & Sojat, Z. (2015). Scalable distributed computing hierarchy: Cloud, fog and dew computing. Open Journal of Cloud Computing (OJCC), 2(1), 16–24.spa
dc.relation.referencesŠojat, Z., & Skala, K. (2016). Views on the role and importance of dew computing in the service and control technology. En 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 164-168). https://doi.org/10.1109/MIPRO.2016.7522131spa
dc.relation.referencesŠojat, Z., & Skala, K. (2017). The dawn of Dew: Dew Computing for advanced living environment. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 347-352). https://doi.org/10.23919/MIPRO.2017.7973447spa
dc.relation.referencesStojkoska, B. R., Trivodaliev, K., & Davcev, D. (2017). Internet of things framework for home care systems. Wireless Communications and Mobile Computing, 2017. https://doi.org/10.1155/2017/8323646spa
dc.relation.referencesAWS Developers. (2017, diciembre 12). AWS Greengrass – Computación de Lambda integrada en dispositivos conectados – Amazon Web Services. Recuperado 12 de diciembre de 2017, a partir de //aws.amazon.com/es/greengrass/ Brezany, P., Ludescher, T., & Feilhauer, T. (2017). Cloud-Dew computing support for automatic data analysis in life sciences. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 365-370). https://doi.org/10.23919/MIPRO.2017.7973450 Cabé, B. (2018). Key Trends from the IoT Developer Survey 2018. Recuperado a partir de https://blogs.eclipse.org/post/benjamin-cab%C3%A9/key-trends-iot-developer-survey-2018 Chang, K.-D., Chen, J.-L., Chen, C.-Y., & Chao, H.-C. (2012). IoT operations management and traffic analysis for Future Internet. En Computing, Communications and Applications Conference (ComComAp), 2012 (pp. 138–142). IEEE. Crnko, N. (2017). Distributed Database System as a base for multilanguage support for legacy software. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 371-374). https://doi.org/10.23919/MIPRO.2017.7973451 Crook, S., MacGillivray, C., & Turner, V. (2017, julio 1). IDC MarketScape: Worldwide IoT Platforms (Software Vendors) 2017 Vendor Assessment. Recuperado 12 de diciembre de 2017, a partir de http://www.idc.com/getdoc.jsp?containerId=US42033517 Deepti Sharma, P. K. (2015). A Detail Review on Cloud, Fog and Dew Computing. International Journal of Science, Engineering and Technology Research (IJSETR), 5(5), 9. Fernández, P. (1996). Determinación del tamaño muestral. Cad Aten Primaria, 3, 138–141. Frincu, M. (2017). Architecting a hybrid cross layer dew-fog-cloud stack for future data-driven cyber-physical systems. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 399-403). https://doi.org/10.23919/MIPRO.2017.7973456 Goleva, R. I., Garcia, N. M., Mavromoustakis, C. X., Dobre, C., Mastorakis, G., & Stainov, R. (2017). Chapter 16 - End-Users Testing of Enhanced Living Environment Platform and Services. En Ambient Assisted Living and Enhanced Living Environments (pp. 427-440). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-805195-5.00016-8 Goleva, R. I., Garcia, N. M., Mavromoustakis, C. X., Dobre, C., Mastorakis, G., Stainov, R., … Trajkovik, V. (2017). Chapter 8 - AAL and ELE Platform Architecture. En Ambient Assisted Living and Enhanced Living Environments (pp. 171-209). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-805195-5.00008-9 Gordienko, Y., Stirenko, S., Alienin, O., Skala, K., Sojat, Z., Rojbi, A., … Jervan, G. (2017). Augmented Coaching Ecosystem for Non-obtrusive Adaptive Personalized Elderly Care on the basis of Cloud-Fog-Dew computing paradigm. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 359-364). https://doi.org/10.23919/MIPRO.2017.7973449 Gremban, K., & Street, C. (2017, noviembre 15). What is Azure IoT Edge. Recuperado 7 de diciembre de 2017, a partir de https://docs.microsoft.com/en-us/azure/iot-edge/how-iot-edge-works Gusev, M. (2017). A dew computing solution for IoT streaming devices. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 387-392). https://doi.org/10.23919/MIPRO.2017.7973454 Gusev, M., & Guseva, A. (2017). State-of-the-art of cloud solutions based on ECG sensors. En IEEE EUROCON 2017 -17th International Conference on Smart Technologies (pp. 501-506). https://doi.org/10.1109/EUROCON.2017.8011162 Huang, D., & Wu, H. (2018). Chapter 6 - Edge Clouds – Pushing the Boundary of Mobile Clouds. En Mobile Cloud Computing (pp. 153-176). Morgan Kaufmann. https://doi.org/10.1016/B978-0-12-809641-3.00008-9 Jóźwiak, L. (2017). Advanced mobile and wearable systems. Microprocessors and Microsystems, 50 (Supplement C), 202-221. https://doi.org/10.1016/j.micpro.2017.03.008 Kholod, I., Efimova, M., Rukavitsyn, A., & Andrey, S. (2017). Time Series Distributed Analysis in IoT with ETL and Data Mining Technologies. En Internet of Things, Smart Spaces, and Next Generation Networks and Systems (pp. 97-108). Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_9 Lorga, M., Feldman, L., Barton, R., Martin, M., Goren, N., & Mahmoudi, C. (2017, septiembre 21). The NIST Definition of Fog Computing. Recuperado 11 de octubre de 2017, a partir de https://csrc.nist.gov/publications/detail/sp/800-191/draft Luchian, E. F., Taut, A., Ivanciu, I. A., Lazar, G., & Dobrota, V. (2017). Mobile wireless sensor network gateway: A raspberry Pi implementation with a VPN backend to OpenStack. En 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM) (pp. 1-5). https://doi.org/10.23919/SOFTCOM.2017.8115561 Mell, P., & Grance, T. (2011, julio 7). The NIST Definition of Cloud Computing. Recuperado 5 de diciembre de 2017, a partir de https://csrc.nist.gov/publications/detail/sp/800-145/final MSV, J. (2017, septiembre 15). Demystifying Edge Computing -- Device Edge vs. Cloud Edge. Recuperado 12 de octubre de 2017, a partir de https://www.forbes.com/sites/janakirammsv/2017/09/15/demystifying-edge-computing-device-edge-vs-cloud-edge/ Mulay, P., Patel, K., & Gauchia, H. G. (2017). Distributed system implementation based on «ants feeding birds» algorithm: Electronics transformation via animals and human. En Detecting and Mitigating Robotic Cyber Security Risks (pp. 51-85). https://doi.org/10.4018/978-1-5225-2154-9.ch005 Patel, H., Chaudhari, R., R Prajapati, K., & A Patel, A. (2017). The Interdependent Part of Cloud Computing:Dew Computing. Podbojec, D., Herynek, B., Jazbec, D., Cvetko, M., Debevc, M., & Kožuh, I. (2017). 3D-based location positioning using the Dew Computing approach for indoor navigation. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 393-398). https://doi.org/10.23919/MIPRO.2017.7973455 Quwaider, M., Al-Alyyoub, M., & Jararweh, Y. (2016). Cloud Support Data Management Infrastructure for Upcoming Smart Cities. Procedia Computer Science, 83, 1232–1237. Ray, P. P. (2017). An Introduction to Dew Computing: Definition, Concept and Implications. IEEE Access, PP(99), 1-1. https://doi.org/10.1109/ACCESS.2017.2775042 Rindos, A., & Wang, Y. (2016). Dew Computing: The Complementary Piece of Cloud Computing. En Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom)(BDCloud-SocialCom-SustainCom), 2016 IEEE International Conferences on (pp. 15–20). IEEE. Recuperado a partir de http://ieeexplore.ieee.org/abstract/document/7723668/ Ristov, S., Cvetkov, K., & Gusev, M. (2016). Implementation of a Horizontal Scalable Balancer for Dew Computing Services. Scalable Computing: Practice and Experience, 17(2), 79–90. Skala, K., Davidovic, D., Afgan, E., Sovic, I., & Sojat, Z. (2015). Scalable distributed computing hierarchy: Cloud, fog and dew computing. Open Journal of Cloud Computing (OJCC), 2(1), 16–24. Šojat, Z., & Skala, K. (2016). Views on the role and importance of dew computing in the service and control technology. En 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 164-168). https://doi.org/10.1109/MIPRO.2016.7522131 Šojat, Z., & Skala, K. (2017). The dawn of Dew: Dew Computing for advanced living environment. En 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 347-352). https://doi.org/10.23919/MIPRO.2017.7973447 Stojkoska, B. R., Trivodaliev, K., & Davcev, D. (2017). Internet of things framework for home care systems. Wireless Communications and Mobile Computing, 2017. https://doi.org/10.1155/2017/8323646 Uehara, M. (2017). Mist Computing: Linking Cloudlet to Fogs. En Computational Science/Intelligence and Applied Informatics (pp. 201-213). Springer, Cham. https://doi.org/10.1007/978-3-319-63618-4_15spa
dc.relation.referencesVogels, W. (2017, junio 7). Unlocking the Value of Device Data with AWS Greengrass. [Blog]. Recuperado 21 de febrero de 2018, a partir de https://www.allthingsdistributed.com/2017/06/unlocking-value-device-data-aws-greengrass.htmlspa
dc.relation.referencesWang, Y. (2017). The Theory and Applications of Dew Computing. En Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering (pp. 317–317). Riverton, NJ, USA: IBM Corp. Recuperado a partir de http://dl.acm.org.aure.unab.edu.co/citation.cfm?id=3172795.3172843spa
dc.relation.referencesWang, Y., & LeBlanc, D. (2016). Integrating SaaS and SaaP with Dew Computing. En Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom)(BDCloud-SocialCom-SustainCom), 2016 IEEE International Conferences on (pp. 590–594). IEEE. Recuperado a partir de http://ieeexplore.ieee.org/abstract/document/7723746/spa
dc.relation.referencesZhou, Y., Zhang, D., & Xiong, N. (2017). Post-cloud computing paradigms: a survey and comparison. Tsinghua Science and Technology, 22(6), 714-732. https://doi.org/10.23919/TST.2017.8195353spa
dc.contributor.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000068845*
dc.contributor.orcidhttps://orcid.org/0000-0002-0159-4889*
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembTelemáticaspa
dc.subject.lembIngeniería de softwarespa
dc.subject.lembComputación en la nubespa
dc.subject.lembInvestigacionesspa
dc.subject.lembAnálisisspa
dc.description.abstractenglishDew Computing or the dew or tear computation has aroused considerable interest in the academy, due to the separation of the processes of distributed computing; where are the layers of Cloud Computing (cloud computing), Fog Computing (fog computing), Edge Computing (edge computing) and finally Dew Computing. These layers are mentioned in descending order (from highest to lowest) with Dew Computing being the closest to the end user. This is done for a better understanding of the technologies and processes that are carried out in them, allowing their differentiation.eng
dc.subject.proposalComputación de nieblaspa
dc.subject.proposalComputación de rocíospa
dc.subject.proposalInternet de las cosasspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*


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