Performance analysis of 6LoWPAN protocol for a food monitoring system

The 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 s...

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Autores:
Piñeres Espitia, Gabriel Dario
aziz, shariq
Estévez‑Ortiz, Francisco
Cama-Pinto, Alejandro
Maleh, yassine
Tipo de recurso:
Article of journal
Fecha de publicación:
2022
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9130
Acceso en línea:
https://hdl.handle.net/11323/9130
https://doi.org/10.1186/s13638-022-02098-3
https://repositorio.cuc.edu.co/
Palabra clave:
6LoWPAN
Wireless sensor networks (WSN)
Routing protocol
Low-power listening (LPL)
Network monitoring and measurements
Flash food
Rights
openAccess
License
© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.
id RCUC2_fed85ce3a4378b1c27a619a8c2f349e7
oai_identifier_str oai:repositorio.cuc.edu.co:11323/9130
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Performance analysis of 6LoWPAN protocol for a food monitoring system
title Performance analysis of 6LoWPAN protocol for a food monitoring system
spellingShingle Performance analysis of 6LoWPAN protocol for a food monitoring system
6LoWPAN
Wireless sensor networks (WSN)
Routing protocol
Low-power listening (LPL)
Network monitoring and measurements
Flash food
title_short Performance analysis of 6LoWPAN protocol for a food monitoring system
title_full Performance analysis of 6LoWPAN protocol for a food monitoring system
title_fullStr Performance analysis of 6LoWPAN protocol for a food monitoring system
title_full_unstemmed Performance analysis of 6LoWPAN protocol for a food monitoring system
title_sort Performance analysis of 6LoWPAN protocol for a food monitoring system
dc.creator.fl_str_mv Piñeres Espitia, Gabriel Dario
aziz, shariq
Estévez‑Ortiz, Francisco
Cama-Pinto, Alejandro
Maleh, yassine
dc.contributor.author.spa.fl_str_mv Piñeres Espitia, Gabriel Dario
aziz, shariq
Estévez‑Ortiz, Francisco
Cama-Pinto, Alejandro
Maleh, yassine
dc.subject.proposal.eng.fl_str_mv 6LoWPAN
Wireless sensor networks (WSN)
Routing protocol
Low-power listening (LPL)
Network monitoring and measurements
Flash food
topic 6LoWPAN
Wireless sensor networks (WSN)
Routing protocol
Low-power listening (LPL)
Network monitoring and measurements
Flash food
description The 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.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-04-18T23:08:22Z
dc.date.available.none.fl_str_mv 2022-04-18T23:08:22Z
dc.date.issued.none.fl_str_mv 2022
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.citation.spa.fl_str_mv Gabriel, 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/s13638-022-02098-3
dc.identifier.issn.spa.fl_str_mv 1687-1472
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/9130
dc.identifier.url.spa.fl_str_mv https://doi.org/10.1186/s13638-022-02098-3
dc.identifier.doi.spa.fl_str_mv 10.1186/s13638-022-02098-3
dc.identifier.eissn.spa.fl_str_mv 1687-1499
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/
identifier_str_mv Gabriel, 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/s13638-022-02098-3
1687-1472
10.1186/s13638-022-02098-3
1687-1499
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/9130
https://doi.org/10.1186/s13638-022-02098-3
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofjournal.spa.fl_str_mv Eurasip Journal on Wireless Communications and Networking
dc.relation.references.spa.fl_str_mv 1. 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. 272–281
2. Z. Allam, Z.A. Dhunny, On big data, artifcial intelligence and smart cities. Cities 89, 80–91 (2019)
3. 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)
4. G. Piñeres-Espitia, A. Mejía-Neira, Technological platforms applied the climatic monitoring. Prospectiva 11(2), 78–87 (2013). https://doi.org/10.15665/rp.v11i2.42
5. 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. 192–206
6. 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/s16070960
7. 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)
8. 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)
9. 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)
10. 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)
11. 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)
12. 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)
13. 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 2017
14. 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)
15. 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)
16. 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/10.1155/2016/2635429
17. 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.2018.8378656
18. 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)
19. 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.2019.03.026
20. 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. 222–234
21. 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. pp1259-1266
22. 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)
23. 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)
24. 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)
25. 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)
26. 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. 341–348
27. 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)
28. 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. 345–349
29. 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)
30. 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)
31. 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 2017
32. 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 2017
33. 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. 440–444
34. 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.2011.6155986
35. 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. 704–709
36. 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. 1–5
37. 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)
38. A. Berguiga, A. Harchay, A. Massaoudi, H. Youssef, FPMIPv6-S: a new network-based mobility management scheme for 6LoWPAN. Internet Things 13, 100045 (2021)
39. 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)
40. 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)
41. 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. 1–6
42. 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)
43. 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. 1314–1318
44. 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/10.1155/2013/924576
45. 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%3e
46. 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.2013.06.041
47. 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)
48. 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)
49. 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)
50. 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.2014.33
51. 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)
52. 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.2012.10.091
53. 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)
54. 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)
55. 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. 1–6
56. 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)
57. 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)
58. 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/10.1177/1550147717722691
59. 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)
60. 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)
61. 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.2014.11.011
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spelling Piñeres Espitia, Gabriel Darioaziz, shariqEstévez‑Ortiz, FranciscoCama-Pinto, AlejandroMaleh, yassine2022-04-18T23:08:22Z2022-04-18T23:08:22Z2022Gabriel, 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/s13638-022-02098-31687-1472https://hdl.handle.net/11323/9130https://doi.org/10.1186/s13638-022-02098-310.1186/s13638-022-02098-31687-1499Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The 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.18 páginasapplication/pdfengSpringer OpenUnited Kingdom© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.Atribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Performance analysis of 6LoWPAN protocol for a food monitoring systemArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttps://jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-022-02098-3Eurasip Journal on Wireless Communications and Networking1. 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. 272–2812. Z. Allam, Z.A. Dhunny, On big data, artifcial intelligence and smart cities. Cities 89, 80–91 (2019)3. 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)4. G. Piñeres-Espitia, A. Mejía-Neira, Technological platforms applied the climatic monitoring. Prospectiva 11(2), 78–87 (2013). https://doi.org/10.15665/rp.v11i2.425. 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. 192–2066. 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/s160709607. 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)8. 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)9. 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)10. 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)11. 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)12. 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)13. 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 201714. 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)15. 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)16. 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/10.1155/2016/263542917. 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.2018.837865618. 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)19. 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.2019.03.02620. 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. 222–23421. 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. pp1259-126622. 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)23. 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)24. 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)25. 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)26. 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. 341–34827. 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)28. 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. 345–34929. 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)30. 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)31. 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 201732. 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 201733. 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. 440–44434. 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.2011.615598635. 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. 704–70936. 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. 1–537. 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)38. A. Berguiga, A. Harchay, A. Massaoudi, H. Youssef, FPMIPv6-S: a new network-based mobility management scheme for 6LoWPAN. Internet Things 13, 100045 (2021)39. 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)40. 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)41. 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. 1–642. 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)43. 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. 1314–131844. 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/10.1155/2013/92457645. 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%3e46. 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.2013.06.04147. 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)48. 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)49. 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)50. 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.2014.3351. 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)52. 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.2012.10.09153. 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)54. 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)55. 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. 1–656. 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)57. 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)58. 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/10.1177/155014771772269159. 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)60. 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)61. 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.2014.11.011181166LoWPANWireless sensor networks (WSN)Routing protocolLow-power listening (LPL)Network monitoring and measurementsFlash foodPublicationORIGINALPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdfPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdfapplication/pdf2053349https://repositorio.cuc.edu.co/bitstreams/6b9d1edd-7b54-40c2-bda7-01d153072ee4/download0eb131a55654e2cc63525ccf1f07ff93MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/808bea5e-52a3-4282-b62c-0bf6a43fdb6b/downloade30e9215131d99561d40d6b0abbe9badMD52TEXTPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdf.txtPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdf.txttext/plain53150https://repositorio.cuc.edu.co/bitstreams/bb074de2-0630-498a-91b4-285425129895/downloada87a33cbb3501bd60c108dedddd16b52MD53THUMBNAILPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdf.jpgPerformance analysis of 6LoWPAN protocol for a flood monitoring system.pdf.jpgimage/jpeg12626https://repositorio.cuc.edu.co/bitstreams/7a92d064-c8b6-4716-8d5a-08aae9fc73c5/downloadc1213e964af3ed3d21240cc1e64683fcMD5411323/9130oai:repositorio.cuc.edu.co:11323/91302024-09-17 14:16:05.706https://creativecommons.org/licenses/by/4.0/© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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