Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions
The campus wireless networks have many users, who have different roles and network requirements, ranging from the use of educational platforms, informative consultations, emails, among others. Currently due to the inefficient use of network resources and little wireless planning, caused by the growt...
- Autores:
-
Hernandez, Leonel
Balmaceda, Nidia
Hernandez, Hugo
Vargas, Carlos
De la Hoz, Emiro
Orellano, Nataly
Vasquez, Emilse
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5272
- Acceso en línea:
- https://hdl.handle.net/11323/5272
https://repositorio.cuc.edu.co/
- Palabra clave:
- Software-Defined Networks SDN
Wireless networks
PPDIOO
Higher education institutions
Optimization
- Rights
- openAccess
- License
- CC0 1.0 Universal
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dc.title.spa.fl_str_mv |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
title |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
spellingShingle |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions Software-Defined Networks SDN Wireless networks PPDIOO Higher education institutions Optimization |
title_short |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
title_full |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
title_fullStr |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
title_full_unstemmed |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
title_sort |
Optimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutions |
dc.creator.fl_str_mv |
Hernandez, Leonel Balmaceda, Nidia Hernandez, Hugo Vargas, Carlos De la Hoz, Emiro Orellano, Nataly Vasquez, Emilse |
dc.contributor.author.spa.fl_str_mv |
Hernandez, Leonel Balmaceda, Nidia Hernandez, Hugo Vargas, Carlos De la Hoz, Emiro Orellano, Nataly Vasquez, Emilse |
dc.subject.spa.fl_str_mv |
Software-Defined Networks SDN Wireless networks PPDIOO Higher education institutions Optimization |
topic |
Software-Defined Networks SDN Wireless networks PPDIOO Higher education institutions Optimization |
description |
The campus wireless networks have many users, who have different roles and network requirements, ranging from the use of educational platforms, informative consultations, emails, among others. Currently due to the inefficient use of network resources and little wireless planning, caused by the growth of the technological infrastructure (which is often due to daily worries, rather than to a lack of preparation by those in charge of managing the network), There are two essential factors that truncate the requirement of having a stable and robust net-work platform. First, the degradation of the quality of services perceived by users, and second, the congestion caused by the high demand for convergent traffic (video, voice, and data). Both factors imply great challenges on the part of the administrators of the network, which in many occasions are overwhelmed by per-manent incidences of instability, coverage, and congestion, as well as the diffi-culty of maintaining it economically. The present investigation seeks to propose a process of optimization of the infrastructure and parameters of the configuration of a wireless network, that allows maximizing the level of satisfaction of the users in Higher Education Institutions. In the first place, it is expected to determine an adequate methodology to estimate the level of satisfaction of the users (defining a mathematical criterion or algorithm based on the study variables [1], character-ize the environment in which the project will be developed, making a complete study of the wireless conditions and implement optimization strategies with soft-ware-defined networks (SDN). SDN is a concept in computer networks that al-lows network management to be carried out efficiently and flexibly, separating the control plane from the data plane into network devices. SDN architecture consists of an infrastructure layer which is a collection of network devices con-nected to the SDN Controller using protocol (OpenFlow) as a protocol [2]. Also, SDN will study traffic patterns on the network as a basis for optimizing network device usage [3]. The phases of the research will be carried out following the life cycle defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Imple-ment, Operate, Optimize) [4]. |
publishDate |
2019 |
dc.date.accessioned.none.fl_str_mv |
2019-09-16T15:59:53Z |
dc.date.available.none.fl_str_mv |
2019-09-16T15:59:53Z |
dc.date.issued.none.fl_str_mv |
2019 |
dc.type.spa.fl_str_mv |
Pre-Publicación |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_816b |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/preprint |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ARTOTR |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_816b |
status_str |
acceptedVersion |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/5272 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
url |
https://hdl.handle.net/11323/5272 https://repositorio.cuc.edu.co/ |
identifier_str_mv |
Corporación Universidad de la Costa REDICUC - Repositorio CUC |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.references.spa.fl_str_mv |
. C. E. Uc-Rios and D. Lara-Rodriguez, “An efficient scheduler for real and non-real time services maximizing satisfied users in wireless networks,” Proc. - Int. Conf. Comput. Commun. Networks, ICCCN, 2011. 2. ONF, “Software-Defined Networking (SDN) Definition - Open Networking Foundation,” ONF. 2018. 3. A. K. Rangisetti and B. R. Tamma, “Software Defined Wireless Networks: A Survey of Issues and Solutions,” Wirel. Pers. Commun., 2017. 4. P. Oppenheimer, Top-down Network Design, 3rd ed. Indianapolis: Cisco Press, 2011. 5. L. Hernandez, G. Jimenez, and C. Baloco, “Characterization of the Use of the Internet of Things in the Institutions of Higher Education of the City of Barranquilla and Its Metropolitan Area,” in HCI International 2018 – Posters’ Extended Abstracts, 2018, vol. 852, pp. 17–24. 6. Y. Zhao, W. Li, J. Wu, and S. Lu, “Quantized conflict graphs for wireless network optimization,” in Proceedings - IEEE INFOCOM, 2015, vol. 26, pp. 2218–2226. 7. T. Yao, X. Guo, Y. Qiu, and L. Ge, “An integral optimization framework for WLAN design,” in International Conference on Communication Technology Proceedings, ICCT, 2013. 8. Cisco Networking Academy, “Cisco Networking Academy,” 2015, 2015. [Online]. Available: http://www.cisco.com/web/learning/netacad/index.html. 9. S. Sezer et al., “INTRODUCTION: WHAT IS SOFTWARE-DEFINED NETWORKING? FUTURE CARRIER NETWORKS Are We Ready for SDN? Implementation Challenges for Software-Defined Networks BACKGROUND: WHY SDN?,” Futur. Carr. Networks, 2013. 10. M. Jammal, T. Singh, A. Shami, R. Asal, and Y. Li, “Software defined networking: State of the art and research challenges,” Comput. Networks, 2014. 11. K. Bakshi, “Considerations for Software Defined Networking (SDN): Approaches and use cases,” in IEEE Aerospace Conference Proceedings, 2013. 12. M. Baird, B. Ng, and W. Seah, “WiFi Network Access Control for IoT Connectivity with Software Defined Networking,” in Proceedings of the 8th ACM on Multimedia Systems Conference - MMSys’17, 2017. 13. Sandhya, Y. Sinha, and K. Haribabu, “A survey: Hybrid SDN,” Journal of Network and Computer Applications. 2017. 14. R. Amin, M. Reisslein, and N. Shah, “Hybrid SDN Networks : A Survey of Existing Approaches,” IEEE Commun. Surv. Tutorials, no. c, pp. 1–34, 2018. 15. S. Haruyama, “Software-Defined Radio Technologies,” … Technol. New Multimed. Syst., 2002. 16. I. Bedhief, M. Kassar, and T. Aguili, “SDN-based architecture challenging the IoT heterogeneity,” in 2016 3rd Smart Cloud Networks and Systems, SCNS 2016, 2017. 17. R. D. R. Fontes, M. Mahfoudi, W. Dabbous, T. Turletti, and C. Rothenberg, “How Far Can We Go? Towards Realistic Software-Defined Wireless Networking Experiments,” Comput. J., 2017. 18. S. M. M. Gilani, T. Hong, W. Jin, G. Zhao, H. M. Heang, and C. Xu, “Mobility management in IEEE 802.11 WLAN using SDN/NFV technologies,” Eurasip J. Wirel. Commun. Netw., 2017. 19. A. Blenk, A. Basta, J. Zerwas, M. Reisslein, and W. Kellerer, “Control Plane Latency with SDN Network Hypervisors: The Cost of Virtualization,” IEEE Trans. Netw. Serv. Manag., 2016. 20. R. Hernandez Sampieri, C. Fernandez Collado, and M. del P. Baptista Lucio, Metodología de la investigación. 2010. |
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CC0 1.0 Universal |
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Universidad de la Costa |
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Corporación Universidad de la Costa |
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Hernandez, LeonelBalmaceda, NidiaHernandez, HugoVargas, CarlosDe la Hoz, EmiroOrellano, NatalyVasquez, Emilse2019-09-16T15:59:53Z2019-09-16T15:59:53Z2019https://hdl.handle.net/11323/5272Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The campus wireless networks have many users, who have different roles and network requirements, ranging from the use of educational platforms, informative consultations, emails, among others. Currently due to the inefficient use of network resources and little wireless planning, caused by the growth of the technological infrastructure (which is often due to daily worries, rather than to a lack of preparation by those in charge of managing the network), There are two essential factors that truncate the requirement of having a stable and robust net-work platform. First, the degradation of the quality of services perceived by users, and second, the congestion caused by the high demand for convergent traffic (video, voice, and data). Both factors imply great challenges on the part of the administrators of the network, which in many occasions are overwhelmed by per-manent incidences of instability, coverage, and congestion, as well as the diffi-culty of maintaining it economically. The present investigation seeks to propose a process of optimization of the infrastructure and parameters of the configuration of a wireless network, that allows maximizing the level of satisfaction of the users in Higher Education Institutions. In the first place, it is expected to determine an adequate methodology to estimate the level of satisfaction of the users (defining a mathematical criterion or algorithm based on the study variables [1], character-ize the environment in which the project will be developed, making a complete study of the wireless conditions and implement optimization strategies with soft-ware-defined networks (SDN). SDN is a concept in computer networks that al-lows network management to be carried out efficiently and flexibly, separating the control plane from the data plane into network devices. SDN architecture consists of an infrastructure layer which is a collection of network devices con-nected to the SDN Controller using protocol (OpenFlow) as a protocol [2]. Also, SDN will study traffic patterns on the network as a basis for optimizing network device usage [3]. The phases of the research will be carried out following the life cycle defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Imple-ment, Operate, Optimize) [4].Institución Universitaria ITSA, Corporación Universitaria Reformada CUR, Corporación Universitaria Latinoamericana CUL, Universidad de la Costa CUC, Universitaria Minuto de Dios UNIMINUTO, Universidad Libre.Hernandez, Leonel-will be generated-orcid-0000-0002-3467-4797-600Balmaceda, NidiaHernandez, HugoVargas, CarlosDe la Hoz, Emiro-will be generated-orcid-0000-0002-4926-7414-600Orellano, NatalyVasquez, EmilseengUniversidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Software-Defined Networks SDNWireless networksPPDIOOHigher education institutionsOptimizationOptimization of a wifi wireless network that maximizes the level of satisfaction of users and allows the use of new technological trends in higher education institutionsPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersion. C. E. Uc-Rios and D. Lara-Rodriguez, “An efficient scheduler for real and non-real time services maximizing satisfied users in wireless networks,” Proc. - Int. Conf. Comput. Commun. Networks, ICCCN, 2011. 2. ONF, “Software-Defined Networking (SDN) Definition - Open Networking Foundation,” ONF. 2018. 3. A. K. Rangisetti and B. R. Tamma, “Software Defined Wireless Networks: A Survey of Issues and Solutions,” Wirel. Pers. Commun., 2017. 4. P. Oppenheimer, Top-down Network Design, 3rd ed. Indianapolis: Cisco Press, 2011. 5. L. Hernandez, G. Jimenez, and C. Baloco, “Characterization of the Use of the Internet of Things in the Institutions of Higher Education of the City of Barranquilla and Its Metropolitan Area,” in HCI International 2018 – Posters’ Extended Abstracts, 2018, vol. 852, pp. 17–24. 6. Y. Zhao, W. Li, J. Wu, and S. Lu, “Quantized conflict graphs for wireless network optimization,” in Proceedings - IEEE INFOCOM, 2015, vol. 26, pp. 2218–2226. 7. T. Yao, X. Guo, Y. Qiu, and L. Ge, “An integral optimization framework for WLAN design,” in International Conference on Communication Technology Proceedings, ICCT, 2013. 8. Cisco Networking Academy, “Cisco Networking Academy,” 2015, 2015. [Online]. Available: http://www.cisco.com/web/learning/netacad/index.html. 9. S. Sezer et al., “INTRODUCTION: WHAT IS SOFTWARE-DEFINED NETWORKING? FUTURE CARRIER NETWORKS Are We Ready for SDN? Implementation Challenges for Software-Defined Networks BACKGROUND: WHY SDN?,” Futur. Carr. Networks, 2013. 10. M. Jammal, T. Singh, A. Shami, R. Asal, and Y. Li, “Software defined networking: State of the art and research challenges,” Comput. Networks, 2014. 11. K. Bakshi, “Considerations for Software Defined Networking (SDN): Approaches and use cases,” in IEEE Aerospace Conference Proceedings, 2013. 12. M. Baird, B. Ng, and W. Seah, “WiFi Network Access Control for IoT Connectivity with Software Defined Networking,” in Proceedings of the 8th ACM on Multimedia Systems Conference - MMSys’17, 2017. 13. Sandhya, Y. Sinha, and K. Haribabu, “A survey: Hybrid SDN,” Journal of Network and Computer Applications. 2017. 14. R. Amin, M. Reisslein, and N. Shah, “Hybrid SDN Networks : A Survey of Existing Approaches,” IEEE Commun. Surv. Tutorials, no. c, pp. 1–34, 2018. 15. S. Haruyama, “Software-Defined Radio Technologies,” … Technol. New Multimed. Syst., 2002. 16. I. Bedhief, M. Kassar, and T. Aguili, “SDN-based architecture challenging the IoT heterogeneity,” in 2016 3rd Smart Cloud Networks and Systems, SCNS 2016, 2017. 17. R. D. R. Fontes, M. Mahfoudi, W. Dabbous, T. Turletti, and C. Rothenberg, “How Far Can We Go? Towards Realistic Software-Defined Wireless Networking Experiments,” Comput. J., 2017. 18. S. M. M. Gilani, T. Hong, W. Jin, G. Zhao, H. M. Heang, and C. Xu, “Mobility management in IEEE 802.11 WLAN using SDN/NFV technologies,” Eurasip J. Wirel. Commun. Netw., 2017. 19. A. Blenk, A. Basta, J. Zerwas, M. Reisslein, and W. Kellerer, “Control Plane Latency with SDN Network Hypervisors: The Cost of Virtualization,” IEEE Trans. Netw. Serv. Manag., 2016. 20. R. Hernandez Sampieri, C. Fernandez Collado, and M. del P. Baptista Lucio, Metodología de la investigación. 2010.PublicationORIGINALOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdfOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdfapplication/pdf924189https://repositorio.cuc.edu.co/bitstreams/aadeada3-4456-4836-affc-0b5ee0d88b70/downloadd4d23725b9ff3c49f78b33e2fe17292dMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/f4de953b-da15-498e-8c3c-11634135d36a/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/f723b5d8-7e54-4f54-8a51-c62c1d4c97ad/download8a4605be74aa9ea9d79846c1fba20a33MD53THUMBNAILOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdf.jpgOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdf.jpgimage/jpeg41492https://repositorio.cuc.edu.co/bitstreams/50cf9063-819d-4af0-9002-60a653c5ee13/download8749141e0e621ff857159c6428377dbbMD55TEXTOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdf.txtOptimization of a WiFi Wireless Network that Maximizes the Level of Satisfaction of Users and Allows the Use of New Technological Trends in Higher Education Institutions.pdf.txttext/plain38658https://repositorio.cuc.edu.co/bitstreams/fd9a4d44-27c7-4790-b4f3-3c3162d99c52/download92b97e17823d17f813a2c4baf4ee1697MD5611323/5272oai:repositorio.cuc.edu.co:11323/52722024-09-17 10:15:46.673http://creativecommons.org/publicdomain/zero/1.0/CC0 1.0 Universalopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |