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A Combined Environmental Monitoring Framework based on WSN Clustering and VANET Edge Computation Offloading

by Basilis Mamalis, Sergios Gerakidis
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 2
Year of Publication: 2024
Authors: Basilis Mamalis, Sergios Gerakidis
10.5120/ijca2024923349

Basilis Mamalis, Sergios Gerakidis . A Combined Environmental Monitoring Framework based on WSN Clustering and VANET Edge Computation Offloading. International Journal of Computer Applications. 186, 2 ( Jan 2024), 33-41. DOI=10.5120/ijca2024923349

@article{ 10.5120/ijca2024923349,
author = { Basilis Mamalis, Sergios Gerakidis },
title = { A Combined Environmental Monitoring Framework based on WSN Clustering and VANET Edge Computation Offloading },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2024 },
volume = { 186 },
number = { 2 },
month = { Jan },
year = { 2024 },
issn = { 0975-8887 },
pages = { 33-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number2/33046-2024923349/ },
doi = { 10.5120/ijca2024923349 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:32.291979+05:30
%A Basilis Mamalis
%A Sergios Gerakidis
%T A Combined Environmental Monitoring Framework based on WSN Clustering and VANET Edge Computation Offloading
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 2
%P 33-41
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless Sensor Networks (WSN) and Vehicular Ad-hoc Networks (VANET) have been extensively used in IoT applications for environmental monitoring, especially in rural and agricultural areas. In this paper we present a novel combined approach which uses both WSN and VANET clustered structures for the efficient gathering and processing of environmental parameters in long eNodeB/RSU-enabled roads/highways, which cross large rural areas. The former (WSNs) is used for traditional sensing and data gathering, whereas the latter (VANET) is used for both (a) performing intermediate processing based on modern edge computation offloading techniques, and (b) propagating the data (either raw data or computed results) to the residing eNodeB/RSUs. Extended experimental measurements, taken via the combined use of SUMO and Veins simulation platforms (and focusing in the air quality monitoring experimental case), demonstrate the high efficiency and scalability of the presented approach over very large deployment areas.

References
  1. D. Kandris, C. Nakas, D. Vomvas, G. Koulouras. Applications of wireless sensor networks: an up-to-date survey, Applied System Innovation, vol. 3, no. 1, p. 14, 2020.
  2. K.S. Adu-Manu, J.D. Abdulai, F. Engmann, M. Akazue, J.K. Appati, G.E. Baiden, G. Sarfo-Kantanka, WSN Architectures for Environmental Monitoring Applications, Journal of Sensors, vol. 2022, Article ID 7823481, 18 pages, 2022.
  3. B. Abidi, A. Jilbab, and M.E. Haziti, Routing protocols for wireless sensor networks: a survey”, in Advances in Ubiquitous Computing, Academic Press, 2020.
  4. M. Baire, A. Melis, M.B. Lodi et al., WSN hardware for automotive applications: preliminary results for the case of public transportation, Electronics, vol. 8, no. 12, p. 1483, 2019.
  5. F. Engmann, F.A. Katsriku, J.D. Abdulai, and K.S. Adu-Manu, Reducing the energy budget in WSN using time series models, Wireless Communications and Mobile Computing, vol. 2020, Article ID 8893064, 15 pages, 2020.
  6. A. Mchergui, T. Moulahi, and S. Zeadally, Survey on artificial intelligence (AI) techniques for vehicular ad-hoc networks (VANETs), In Vehicular Communications, volume 1, article 100403, 2022.
  7. H. Yin, Y. Cao, B. Marelli, X. Zeng, A.J. Mason, and C. Cao, Soil sensors and plant wearables for smart and precision agriculture, Advanced Materials, vol. 33, no. 20, 2021.
  8. K.S. Adu-Manu, C. Tapparello, W. Heinzelman, F.A. Katsriku, and J.D. Abdulai, Water quality monitoring using wireless sensor networks, ACM Transactions on Sensor Networks (TOSN), vol. 13, no. 1, pp. 1–41, 2017.
  9. J.O. Ighalo, A.G. Adeniyi, and G. Marques, Internet of things for water quality monitoring and assessment: a comprehensive review, Studies in Computational Intelligence, vol. 912, pp. 245–259, 2021.
  10. V. Lakshmikantha, A. Hiriyannagowda, A. Manjunath, A. Patted, J. Basavaiah, and A. A. Anthony, IoT based smart water quality monitoring system, Global Transitions Proceedings, vol. 2, no. 2, pp. 181–186, 2021.
  11. F. Jan, N. Min-Allah, and D. Düştegör, Iot based smart water quality monitoring: recent techniques, trends and challenges for domestic applications, Water, vol. 13, no. 13, p. 1729, 2021.
  12. R. Kumar, S. Goel, V. Sharma, L. Garg, K. Srinivasan, N. Julka, A multifaceted Vigilare system for intelligent transportation services in smart cities, IEEE Internet of Things Magazine, vol. 3, no. 4, pp. 76–80, 2020.
  13. A. Lanzolla and M. Spadavecchia, Wireless sensor networks for environmental monitoring, Sensors, vol.21, no.4, pp.1–3, 2021.
  14. F. Engmann, K. S. Adu-Manu, J.-D. Abdulai, and F. A. Katsriku, Applications of prediction approaches in wireless sensor networks, in Wireless Sensor Networks-Design, Deployment and Applications, Intech Open, 2021.
  15. B. Senapati, P. Khilar, and R. Swain, “Environmental monitoring through Vehicular Ad Hoc Network: A productive application for smart cities”, International Journal of Communication Systems, Wiley, Volume 34, Issue 18, 2021.
  16. B.R. Senapati, R.R. Swain, P.M. Khilar. Environmental monitoring under uncertainty using smart vehicular ad hoc network. Smart Intelligent Computing and Applications: Springer; 2020:229-238.
  17. T. Tsuji, N. Nagaoka, M. Watanabe, H. Hattori. Vehicle environment monitoring system. US Patent 6,327,536; 2001.
  18. B.R. Senapati, P.M. Khilar, R.R Swain. Fire controlling under uncertainty in urban region using smart vehicular ad hoc network. Wirel PersCommun. 2021;116(3):2049-2069.
  19. K. Ashokkumar, B. Sam, R. Arshadprabhu, R. Britto. Cloud based intelligent transport system. Procedia Comput Sci. 2015;50:58-63.
  20. E. Skondras, A. Michalas, and D.D. Vergados. Mobility management on 5G vehicular cloud computing systems. Veh Commun. 2019;16:15-44.
  21. Z. Alazawi, S. Altowaijri, R. Mehmood, M.B. Abdljabar. Intelligent disaster management system based on cloud-enabled vehicular networks. In 11th Intl. Conf. on Telecommunications IEEE. St. Petersburg, Russia; 2011:361-368.
  22. R. Yu, Y. Zhang, S. Gjessing, W. Xia, K. Yang. Toward cloud-based vehicular networks with efficient resource management. arXiv preprint arXiv:1308.6208; 2013.
  23. R. Oliveira, C. Montez, A. Boukerche, M.S. Wangham. Reliable data dissemination protocol for VANET traffic safety applications. Ad Hoc Netw. 2017;63:30-44.
  24. M. Milojevic, V. Rakocevic. Distributed road traffic congestion quantification using cooperative VANETs. In: 2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET) IEEE; 2014:203-210.
  25. S. Boussoufa-Lahlah, F. Semchedine, ansd L. Bouallouche-Medjkoune. Geographic routing protocols for vehicular ad hoc networks (VANETs): A survey. Veh Commun. 2018;11:20-31.
  26. R. Kumar, M. Dave. A comparative study of various routing protocols in VANET. arXiv preprint arXiv:1108.2094; 2011.
  27. S. Singh, S. Agrawal. VANET routing protocols: issues and challenges. In: 2014 Recent Advances in Engineering and Computational Sciences (RAECS) IEEE. Chandigarh, India; 2014:1-5.
  28. B. Mamalis, “Prolonging Network Lifetime in Wireless Sensor Networks with Path-Constrained Mobile Sink”, in International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 5, No. 10, pp. 82-91, 2014.
  29. L. Sotiriadis, B. Mamalis and G. Pantziou, “Stable and Secure Clustering for Internet of Vehicles with RSU-assisted Maintenance and Trust Management”, in Proceedings of the 25th Panhellenic Conference in Informatics (PCI 2021), ACM ICPS Series, pp. 124-129, Volos, Greece, Nov. 26-28, 2021.
  30. L. Sotiriadis, B. Mamalis and G. Pantziou, “A Cluster-based Virtual Edge Computation Offloading Scheme for MEC-enabled Vehicular Networks”, in Proceedings of the 26th Panhellenic Conference in Informatics (PCI 2022), ACM ICPS Series, Athens, Greece, Nov. 27-29, 2022.
  31. Wikipedia – Air Quality Index. Retrieved November 16, 2023, from https://en.wikipedia.org/wiki/Air_quality_index.
  32. EPA United States Environmental Protection Agency. Retrieved from https://www.epa.gov/air-quality.
  33. A.K.G. Kanchan, and G. Pramila. 2015. A Review on Air Quality Indexing System, Asian Journal of Atmospheric Environment Vol. 9-2, pp. 101-113.
  34. E.Y. Bezuglaya,, A.B. Shchutskaya, and I.V. Smirnova. 1993. Air Pollution Index and Interpretation of Measurements of Toxic Pollutant Concentrations, In Atmospheric Environment 27, 773-779.
  35. Prana Air – What is Air Quality Index (AQI) & How Is It Calculated. Retrieved from https://pranaair.com/blog/what-is-air-quality-index-aqi-and-its-calculation/.
  36. American Lung Association – Air Quality Index: Using AQI information to protect yourself from outdoor air pollution. Retrieved from https://www.lung.org/clean-air/outdoors/air-quality-index.
  37. Air Now – Technical Assistance Document for the Reporting of Daily Air Quality. Retrieved from https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf.
  38. Veins. The open source vehicular network simulation framework. Accessed: Sept. 7, 2022. https://veins.car2x.org/
  39. SUMO. Simulation of Urban Mobility. Accessed: Sept. 7, 2022. http://sumo.dlr.de/wiki/Simulation_of_Urban_Mobility
  40. Castalia – A simulator for Wireless Sensor Networks and Body Area Networks. http://castalia.npc.nicta.com.au
Index Terms

Computer Science
Information Sciences

Keywords

Wireless Sensor Network Vehicular Ad-hoc Network Node Clustering Network Lifetime Virtual Edge Computing Road Side Unit Computation Offloading

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