Mr CRAIG STEWART c.stewart35@rgu.ac.uk
Research Student
An investigation into routing protocols for real-time sensing of subsurface oil wells.
Stewart, Craig; Fough, Nazila; Prabhu, Radhakrishna
Authors
Dr Nazila Fough n.fough1@rgu.ac.uk
Lecturer
Professor Radhakrishna Prabhu r.prabhu@rgu.ac.uk
Professor
Contributors
Maurizio Valle
Editor
Christian Gianoglio
Editor
Edoardo Ragusa
Editor
Lucia Seminara
Editor
Dirk Lehmhus
Editor
Stefan Bosse
Editor
Ali Ibrahim
Editor
Klaus-Dieter Thoben
Editor
Abstract
Pervasive computing has transformed society, and there is a desire to extend this mass data connectivity to the ocean, especially by energy companies seeking real-time sensor data from assets such as oil wells and pipelines. As evidenced by the Deepwater Horizon, Piper Alpha, and other disasters, failure of these assets can result in disaster, with human lives lost and financial consequences. To avoid these dangers, energy companies are keen on using underwater wireless sensor networks to achieve real-time asset monitoring so that maintenance and analysis can be proactive in the face of hazards or natural seismic activity. Generally, acoustic transmission technology is utilised to communicate with emerging ad-hoc UWSN, an established technology characterised by large coverage areas and reliable connectivity at the expense of high energy consumption and low operational bandwidth. Given that it is impossible to increase the speed of sound without altering the underwater channel itself physically in terms of temperature, salinity, noise removal and pressure manipulation, maximising end to end delivery time in each scenario is largely dependent on the hardware design involved and the selected protocol on the network and data link layers as well as the physical topology of the network. This simulation driven investigation aims to establish how routing technique and topology choice effects end-to-end delivery times in populated, active deep water oil drilling areas such as the Gulf of Mexico (source of the infamous Deepwater Horizon incident), the North Sea (source of the Piper Alpha Incident), the Atlantic Ocean and the South China Sea. The simulation was carried out in NS-3/Aquasim-NG and ascertained that a layered topology of fixed position nodes with Depth Based Routing (DBR) would be optimal for time critical scenarios achieving the best time between sink and source and therefore the best option for a quick response to a hazard when compared to Hop-to-Hop Vector Based Forward (HH-VBF).
Citation
STEWART, C., FOUGH, N. and PRABHU, R. 2022. An investigation into routing protocols for real-time sensing of subsurface oil wells. In Valle, M., Lehmhus, D., Gianoglio, C. et al. (eds.) Advances in system-integrated intelligence: proceedings of the 6th International conference on system-integrated intelligence 2022 (SysInt 2022), 7-9 September 2022, Genova, Italy. Lecture notes in networks and systems (LNNS), 546. Cham: Springer [online], pages 689-699. Available from: https://doi.org/10.1007/978-3-031-16281-7_65
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 6th International conference on System-integrated intelligence 2022 (SysInt 2022) |
Start Date | Sep 7, 2022 |
End Date | Sep 9, 2022 |
Acceptance Date | Jul 5, 2022 |
Online Publication Date | Sep 4, 2022 |
Publication Date | Dec 31, 2022 |
Deposit Date | Sep 14, 2022 |
Publicly Available Date | Sep 5, 2023 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Pages | 689-699 |
Series Title | Lecture notes in network and systems (LNNS) |
Series Number | 546 |
Series ISSN | 2367-3370; 2367-3389 |
Book Title | Advances in system-integrated intelligence: proceedings of the 6th International conference on system-integrated intelligence 2022 (SysInt 2022), 7-9 September 2022, Genova, Italy |
ISBN | 9783031162800 |
DOI | https://doi.org/10.1007/978-3-031-16281-7_65 |
Keywords | IOT; Routing techniques; UIOT; Underwater Sensor Networks (UWSU) |
Public URL | https://rgu-repository.worktribe.com/output/1752988 |
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Copyright Statement
This is a post-peer-review, pre-copyedited version of an article published in Advances in System-Integrated Intelligence. The final authenticated version is available online at: https://doi.org/10.1007/978-3-031-16281-7_65 . This accepted manuscript is subject to Springer Nature's AM terms of use [https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms].
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