Mostrar el registro sencillo del ítem

dc.contributor.authorPiñeres Espitia, Gabriel Dariospa
dc.contributor.authoraziz, shariqspa
dc.contributor.authorEstévez‑Ortiz, Franciscospa
dc.contributor.authorCama-Pinto, Alejandrospa
dc.contributor.authorMaleh, yassinespa
dc.date.accessioned2022-04-18T23:08:22Z
dc.date.available2022-04-18T23:08:22Z
dc.date.issued2022
dc.identifier.citationGabriel, PE., Butt, S.A., Francisco, EO. et al. Performance analysis of 6LoWPAN protocol for a flood monitoring system. J Wireless Com Network 2022, 16 (2022). https://doi.org/10.1186/s13638-022-02098-3spa
dc.identifier.issn1687-1472spa
dc.identifier.urihttps://hdl.handle.net/11323/9130spa
dc.description.abstractThe internet of things is a disruptive technology that has been applied as a solution to problems in many fields of monitoring environmental variables. It is supported by technologies such as wireless sensor networks, which offer many protocols and hardware platforms in the market today. Protocols such as 6LoWPAN are novel, so this work focuses on determining whether its implementation on TelosB mote is feasible; these would be placed on an experimental deployment for a particular scenario of flash floods in a sector known as “La Brigada”, in the city of Barranquilla. This proposal has not been evaluated in Colombia for this type of application, and no similar work has been done for this type of scenario. For the evaluation of 6LoWPAN, a deployment with two end nodes and a sink node has been designed, due to the monitoring section under study; 5-min tests are proposed where through round trip time traffic PINGv6 packets are generated back and forth (Echo) between a sink node and two end nodes. The results are based on the evaluation of metrics such as delay and ping packet request/response rate. The performance of these metrics is subject to test scenarios that vary according to distance, packet size, and channel scan time. Two routing options, static or dynamic, are also proposed for this application case. The tests performed yielded results in terms of better performance in the test scenarios for packets with an average size of 120 B and channel monitoring times of 1024 ms. Likewise, the use of the TelosB platform was validated as a viable and innovative option for a monitoring scenario to flash floods in short stretches of the city of Barranquilla—Colombia. This study is important because it can provide information on the use of the TelosB platform as a valid solution for similar application scenarios; furthermore, the tests performed can be replicated in similar studies to evaluate congestion, power consumption, routing, topologies, and other metrics. This study is providing a road map for the research community to follow the simulation scenario to apply the test to their own studies. This work also provides the guidelines for similar researchers to monitor the flood in their own regions and then compare their results with this study.eng
dc.format.extent18 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherSpringer Openspa
dc.rights© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.spa
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.titlePerformance analysis of 6LoWPAN protocol for a food monitoring systemeng
dc.typeArtículo de revistaspa
dc.identifier.urlhttps://doi.org/10.1186/s13638-022-02098-3spa
dc.source.urlhttps://jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-022-02098-3spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doi10.1186/s13638-022-02098-3spa
dc.identifier.eissn1687-1499spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.publisher.placeUnited Kingdomspa
dc.relation.ispartofjournalEurasip Journal on Wireless Communications and Networkingspa
dc.relation.references1. V.H. Puar, C.M. Bhatt, D.M. Hoang, D.N. Le, Communication in internet of things, in Information Systems Design and Intelligent Applications (Springer, Singapore, 2018), p. 272–281spa
dc.relation.references2. Z. Allam, Z.A. Dhunny, On big data, artifcial intelligence and smart cities. Cities 89, 80–91 (2019)spa
dc.relation.references3. R. Bock, Evaluation of network conditions on the performance of an Industrial IoT control and monitoring system. PhD diss. (North-West University, South Africa, 2021)spa
dc.relation.references4. G. Piñeres-Espitia, A. Mejía-Neira, Technological platforms applied the climatic monitoring. Prospectiva 11(2), 78–87 (2013). https://doi.org/10.15665/rp.v11i2.42spa
dc.relation.references5. B. Avellaneda, D.R. Ramón, E.R. González, C.A. Collazos-Morales, P. Ariza-Colpas, Reasonable non-conventional generator of random linear chains based on a simple self-avoiding walking process: a statistical and fractal analysis, in International Conference on Computational Science and Its Applications (Springer, Cham, 2021), p. 192–206spa
dc.relation.references6. F. Estevez, P. Glosekoetter, J. González, DARAL: a dynamic and adaptive routing algorithm for wireless sensor net‑works. Sensors 16(7), 960 (2016). https://doi.org/10.3390/s16070960spa
dc.relation.references7. M. Bouaziz, A. Rachedi, A survey on mobility management protocols in wireless sensor networks based on 6LoW‑PAN technology. Comput. Commun. 74, 3–15 (2016)spa
dc.relation.references8. A.C. Paola, A.M.C. Eduardo, P.M.M. Alberto, V.D.D. Andrés, M.O.R. Cesar, S.M. Hernando, B.S. Aziz, Real-time monitoring system for the detection of saline wedge in the Magdalena River-Colombia. Proc. Comput. Sci. 191, 391–396 (2021)spa
dc.relation.references9. B.N. Silva, M. Khan, K. Han, Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustain. Cities Soc. 38, 697–713 (2018)spa
dc.relation.references10. S. Malhotra, C.P. SIngh, A. Kumar, Power optimization and network congestion controlling technique for an Iot enabled smartbin for smart cities. SPAST Abstracts 1(01) (2021)spa
dc.relation.references11. A. Cama-Pinto, G. Piñeres-Espitia, Z. Comas-González, J. Zapata-Vélez, F. Gómez-Mula, Design of a monitoring net‑work of meteorological variables related to tornadoes in Barranquilla-Colombia and its metropolitan area. Ingeniare. Revista chilena de ingeniería. 24(4), 585–598 (2017)spa
dc.relation.references12. X. Liu, Z. Sheng, C. Yin, F. Ali, D. Roggen, Performance analysis of routing protocol for low power and lossy networks (RPL) in large scale networks. IEEE Internet Things J. 4(6), 2172–2185 (2017)spa
dc.relation.references13. El Heraldo, Proyecto universitario sobre arroyos será fnanciado por Colciencias (2013). https://www.elheraldo.co/local/proyecto-universitario-sobre-arroyos-sera-fnanciado-por-colciencias-103883. Accessed 6 Nov 2017spa
dc.relation.references14. D. Puthal, S. Nepal, R. Ranjan, J. Chen, A dynamic prime number based efcient security mechanism for big sensing data streams. J. Comput. Syst. Sci. 83(1), 22–42 (2017)spa
dc.relation.references15. S. Verma, Y. Kawamoto, Z.M. Fadlullah, H. Nishiyama, N. Kato, A survey on network methodologies for real-time analytics of massive IoT data and open research issues. IEEE Commun. Surv. Tutor. 19(3), 1457–1477 (2017)spa
dc.relation.references16. M. Khan, A. Lodhi, A. Rehman, A. Khan, F. Hussain, Sink-to-sink coordination framework using RPL: routing protocol for low power and lossy networks. J Sens. 11(4), 2002–2019 (2016). https://doi.org/10.1155/2016/2635429spa
dc.relation.references17. V. Chandrasekar, H. Chen, B. Philips, DFW urban radar network observations of foods, tornadoes and hail storms, in 2018 IEEE Radar Conference (RadarConf18), Oklahoma City (2018), p. 0765–0770. https://doi.org/10.1109/RADAR.2018.8378656spa
dc.relation.references18. L. Ortega-Gonzalez, M. Acosta-Coll, G. Piñeres-Espitia, S.A. Butt, Communication protocols evaluation for a wireless rainfall monitoring network in an urban area. Heliyon 7, e07353 (2021)spa
dc.relation.references19. C. Corral, M. Berenguer, D. Sempere-Torres, L. Poletti, F. Silvestro, N. Rebora, Comparison of two early warning sys‑ tems for regional fash food hazard forecasting. J. Hydrol. (2019). https://doi.org/10.1016/j.jhydrol.2019.03.026spa
dc.relation.references20. S. López-Torres, H. López-Torres, J. Rocha-Rocha, S.A. Butt, M.I. Tariq, C. Collazos-Morales, G. Piñeres-Espitia, IoT monitoring of water consumption for irrigation systems using SEMMA methodology, in International Conference on Intelligent Human Computer Interaction (Springer, Cham, 2019), p. 222–234spa
dc.relation.references21. N. Yaacob, N. Tajudin, A.M. Azize, Rainfall-landslide early warning system (RLEWS) using TRMM precipitation estimates. Indonesian J. Electric. Eng. Comput. Sci. 13(3), 1259–1266 (2019). https://doi.org/10.11591/ijeecs.v13.i3. pp1259-1266spa
dc.relation.references22. S. Segoni, L. Piciullo, S.L. Gariano, A review of the recent literature on rainfall thresholds for landslide occurrence. Landslides 15(8), 1483–1501 (2018)spa
dc.relation.references23. V.H. Lai, V.C. Tsai, M.P. Lamb, T.P. Ulizio, A.R. Beer, The seismic signature of debris fows: fow mechanics and early warning at Montecito, California. Geophys. Res. Lett. 45(11), 5528–5535 (2018)spa
dc.relation.references24. M. Azam, H. San Kim, S.J. Maeng, Development of food alert application in Mushim stream watershed Korea. Int. J. Disast. Risk Reduct. 21, 11–26 (2017)spa
dc.relation.references25. C. Cecioni, G. Bellotti, A. Romano, A. Abdolali, P. Sammarco, L. Franco, Tsunami early warning system based on realtime measurements of hydro-acoustic waves. Proc. Eng. 70, 311–320 (2014)spa
dc.relation.references26. B.S.B. Dewantara, F. Ardilla, Early warning and IoT-based reporting system for mobile trash bin robot application, in 2018 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) (IEEE, 2018), p. 341–348spa
dc.relation.references27. N.-A. Maspo, A.N. Harun, M. Goto, M.N.M. Nawi, N.A. Haron, Development of internet of thing (IoT) technology for food prediction and early warning system (EWS). Int. J. Innov. Technol. Explor. Eng. 8(4S), 219–228 (2019)spa
dc.relation.references28. R.W. Randhawa, R. Mahmood, T. Ahmad, AquaEye: a low cost food early warning system for developing countries, in 2018 International Conference on Frontiers of Information Technology (FIT) (IEEE, 2018), p. 345–349spa
dc.relation.references29. E. Intrieri, G. Gigli, T. Gracchi, M. Nocentini, L. Lombardi, F. Mugnai, A. Fornaciai, Application of an ultra-wide band sensor-free wireless network for ground monitoring. Eng. Geol. 238, 1–14 (2018)spa
dc.relation.references30. M. Acosta-Coll, F. Ballester-Merelo, M. Martinez-Peiró, D. la Hoz-Franco, Real-time early warning system design for pluvial fash foods—a review. Sensors 18(7), 2255 (2018)spa
dc.relation.references31. J. Arrieta, Y. Fernández, Estimación De Los Caudales Del Arroyo La Segunda Brigada II Para Diferentes Períodos De Retorno Aplicando La Herramienta Computacional Epa-Swmm (2015). http://hdl.handle.net/11323/490. Accessed 29 Nov 2017spa
dc.relation.references32. A. Raad, D. Villa, Diseño y desarrollo de una aplicación móvil para dispositivos android para un sistema de alerta temprana de los arroyos de la ciudad de Barranquilla (2014). http://hdl.handle.net/11323/238. Accessed 29 Nov 2017spa
dc.relation.references33. A. Chatap, S. Sirsikar, Review on various routing protocols for heterogeneous wireless sensor network, in 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) (2017), p. 440–444spa
dc.relation.references34. J. He, X. Huang, Increased interoperability: evolution of 6LoWPAN-based web application, in 4th IEEE International Conference on Broadband Network and Multimedia Technology (IC-BNMT), Shenzhen (2011), p. 507–510. https://doi. org/10.1109/ICBNMT.2011.6155986spa
dc.relation.references35. D.W. Courtney, P. Thulasiraman, Implementation of secure 6LoWPAN communications for tactical wireless sensor networks, in 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (IEEE, 2016), p. 704–709spa
dc.relation.references36. S.O Ooko, J. Kadam’manja, M.G. Uwizeye, D. Lemma, Security issues in IPv6 over Low-power wireless personal area networks (6LoWPAN): a review, in 2020 21st International Arab Conference on Information Technology (ACIT) (IEEE, 2020), p. 1–5spa
dc.relation.references37. U. Shaf, R. Mumtaz, J. García-Nieto, S.A. Hassan, S.A.R. Zaidi, N. Iqbal, Precision agriculture techniques and practices: from considerations to applications. Sensors 19(17), 3796 (2019)spa
dc.relation.references38. A. Berguiga, A. Harchay, A. Massaoudi, H. Youssef, FPMIPv6-S: a new network-based mobility management scheme for 6LoWPAN. Internet Things 13, 100045 (2021)spa
dc.relation.references39. H.A.A. Al-Kashoash, H.M. Amer, L. Mihaylova, A.H. Kemp, Optimization-based hybrid congestion alleviation for 6LoW‑ PAN networks. IEEE Internet Things J. 4(6), 2070–2081 (2017)spa
dc.relation.references40. Y. Yang, Wu. Longfei, G. Yin, L. Li, H. Zhao, A survey on security and privacy issues in internet-of-things. IEEE Internet Things J. 4(5), 1250–1258 (2017)spa
dc.relation.references41. T. Muhammad, G. Abbas, Z.H. Abbas. LAS-6LE: a lightweight authentication scheme for 6LoWPAN environments, in 2020 14th International Conference on Open Source Systems and Technologies (ICOSST) (IEEE, 2020), p. 1–6spa
dc.relation.references42. F. Farshad, A.M. Rahmani, K. Mankodiya, M. Badaroglu, G.V. Merrett, P. Wong, B. Farahani, Internet-of-things and big data for smarter healthcare: from device to architecture, applications and analytics. Future Gen. Comput. Syst. 78, 583–586 (2018)spa
dc.relation.references43. H. Erdol, S. Gormus, M.C. Aydogdu, A novel energy aware routing function for internet of things networks, in 2017 10th International Conference on Electrical and Electronics Engineering (ELECO) (IEEE, 2017), p. 1314–1318spa
dc.relation.references44. A. Efendi, S. Oh, A. Negara, D. Choi, Battery-less 6LoWPAN-based wireless home automation by use of energy har‑ vesting. Int. J. Distrib. Sens. Netw. 9, 7 (2013). https://doi.org/10.1155/2013/924576spa
dc.relation.references45. F. Montoya, J. Gómez, A. Cama-Pinto, A. Zapata-Sierra, F. Martínez, J. De La Cruz, F. Manzano-Agugliaro, A monitor‑ ing system for intensive agriculture based on mesh networks and the android system. Comput. Electron. Agric. 99, 14–20 (2013). https://doi.org/10.1016/j.compag.2013.08.028%3espa
dc.relation.references46. A. Cama-Pinto, F. Montoya, J. Gómez, J. De La Cruz, F. Manzano-Agugliaro, Integration of communication technolo‑ gies in sensor networks to monitor the Amazon environment. J. Clean. Prod. 59, 32–42 (2013). https://doi.org/10. 1016/j.jclepro.2013.06.041spa
dc.relation.references47. G. Pau, V.M. Salerno, Wireless sensor networks for smart homes: a fuzzy-based solution for an energy-efective duty cycle. Electronics 8(2), 131 (2019)spa
dc.relation.references48. X. Fu, G. Fortino, P. Pace, G. Aloi, W. Li, Environment-fusion multipath routing protocol for wireless sensor networks. Inform. Fusion 53, 4–19 (2020)spa
dc.relation.references49. R. Singh, B. Sikdar, A receiver initiated low delay MAC protocol for wake-up radio enabled wireless sensor networks. IEEE Sens. J. 20(22), 13796–13807 (2020)spa
dc.relation.references50. A. Nahas, S. Duquennoy, V. Iyer, T. Voigt, Low-power listening goes multi-channel, in IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS) (2014), p. 2–9. https://doi.org/10.1109/DCOSS.2014.33spa
dc.relation.references51. H. Lamaazi, N. Benamar, A comprehensive survey on enhancements and limitations of the RPL protocol: a focus on the objective function. Ad Hoc Netw. 96, 102001 (2020)spa
dc.relation.references52. S. Sankar Bhunia, S. Kumar Das, S. Roy, N. Mukherjee, An approach to manage mobility of sensor nodes in sensorgrid infrastructure. Proc. Technol. 6, 754–762 (2012). https://doi.org/10.1016/j.protcy.2012.10.091spa
dc.relation.references53. J. Santos, J.J. Rodrigues, B.M. Silva, J. Casal, K. Saleem, V. Denisov, An IoT-based mobile gateway for intelligent per‑ sonal assistants on mobile health environments. J. Netw. Comput. Appl. 71, 194–204 (2016)spa
dc.relation.references54. J. Shreyas, H. Singh, S. Tiwari, N.N. Srinidhi, S.D. Kumar, CAFOR: congestion avoidance using fuzzy logic to fnd an optimal routing path in 6LoWPAN networks. J. Reliab. Intell. Environ. 7, 1–16 (2021)spa
dc.relation.references55. T.W. Ching, A.H.M. Aman, W.M.H. Azamuddin, H. Sallehuddin, Z.S. Attarbashi, Performance Analysis of Internet of Things Routing Protocol for Low Power and Lossy Networks (RPL): Energy, Overhead and Packet Delivery, in 2021 3rd International Cyber Resilience Conference (CRC) (IEEE, 2021). p. 1–6spa
dc.relation.references56. N. Hoque, M.H. Bhuyan, R.C. Baishya, D.K. Bhattacharyya, J.K. Kalita, Network attacks: taxonomy, tools and systems. J. Netw. Comput. Appl. 40, 307–324 (2014)spa
dc.relation.references57. F. Montoya, J. Gomez, F. Manzano-Agugliaro, A. Cama, A. García-Cruz, J. De La Cruz, 6LoWSoft: a software suite for the design of outdoor environmental measurements. J. Food Agric. Environ. 11(3–4), 2584–2586 (2013)spa
dc.relation.references58. A. Cama-Pinto, G. Piñeres-Espitia, J. Caicedo-Ortiz, E. Ramírez-Cerpa, L. Betancur-Agudelo, F. Gómez-Mula, Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules. Int. J. Distrib. Sens. Netw. 13(7), 1–10 (2017). https://doi.org/10.1177/1550147717722691spa
dc.relation.references59. T. Dinh, Y. Kim, T. Gu, A.V. Vasilakos, An adaptive low-power listening protocol for wireless sensor networks in noisy environments. IEEE Syst. J. 12(3), 2162–2173 (2017)spa
dc.relation.references60. B.L.R. Stojkoska, K.V. Trivodaliev, A review of internet of things for smart home: challenges and solutions. J. Clean. Prod. 140, 1454–1464 (2017)spa
dc.relation.references61. N. Baccour, A. Koubâa, H. Youssef, M. Alves, Reliable link quality estimation in low-power wireless networks and its impact on tree-routing. Ad Hoc Netw. 27, 1–25 (2015). https://doi.org/10.1016/j.adhoc.2014.11.011spa
dc.subject.proposal6LoWPANeng
dc.subject.proposalWireless sensor networks (WSN)eng
dc.subject.proposalRouting protocoleng
dc.subject.proposalLow-power listening (LPL)eng
dc.subject.proposalNetwork monitoring and measurementseng
dc.subject.proposalFlash foodeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.relation.citationendpage18spa
dc.relation.citationstartpage1spa
dc.relation.citationissue16spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

  • Artículos científicos [3154]
    Artículos de investigación publicados por miembros de la comunidad universitaria.

Mostrar el registro sencillo del ítem

© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.
Excepto si se señala otra cosa, la licencia del ítem se describe como © 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.