A Survey on Efficient Routing Strategies For The Internet of Underwater Things (IoUT)

The Internet of Underwater Things (IoUT) is an emerging technology that promised to connect the underwater world to the land internet. It is enabled via the usage of the Underwater Acoustic Sensor Network (UASN). Therefore, it is affected by the challenges faced by UASNs such as the high dynamics of the underwater environment, the high transmission delays, low bandwidth, high-power consumption, and high bit error ratio. Due to these challenges, designing an efficient routing protocol for the IoUT is still a trade-off issue. In this paper, we discuss the specific challenges imposed by using UASN for enabling IoUT, we list and explain the general requirements for routing in the IoUT and we discuss how these challenges and requirements are addressed in literature routing protocols. Thus, the presented information lays a foundation for further investigations and futuristic proposals for efficient routing approaches in the IoUT

Green Communication for Underwater Wireless Sensor Networks: Triangle Metric Based Multi-Layered Routing Protocol

[EN] In this paper, we propose a non-localization routing protocol for underwater wireless sensor networks (UWSNs), namely, the triangle metric based multi-layered routing protocol (TM2RP). The main idea of the proposed TM2RP is to utilize supernodes along with depth information and residual energy to balance the energy consumption between sensors. Moreover, TM2RP is the first multi-layered and multi-metric pressure routing protocol that considers link quality with residual energy to improve the selection of next forwarding nodes with more reliable and energy-efficient links. The aqua-sim package based on the ns-2 simulator was used to evaluate the performance of the proposed TM2RP. The obtained results were compared to other similar methods such as depth based routing (DBR) and multi-layered routing protocol (MRP). Simulation results showed that the proposed protocol (TM2RP) obtained better outcomes in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay.This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah (under grant no. DF-524-156-1441). The authors, therefore, gratefully acknowledge DSR for the technical and financial supportKhasawneh, AM.; Kaiwartya, O.; Lloret, J.; Abuaddous, HY.; Abualigah, L.; Shinwan, MA.; Al-Khasawneh, MA.... (2020). Green Communication for Underwater Wireless Sensor Networks: Triangle Metric Based Multi-Layered Routing Protocol. Sensors. 20(24):1-23. https://doi.org/10.3390/s20247278123202

Review on energy efficient opportunistic routing protocol for underwater wireless sensor networks

Currently, the Underwater Sensor Networks (UWSNs) is mainly an interesting area due to its ability to provide a technology to gather many valuable data from underwater environment such as tsunami monitoring sensor, military tactical application, environmental monitoring and many more. However, UWSNs is suffering from limited energy, high packet loss and the use of acoustic communication. In UWSNs most of the energy consumption is used during the forwarding of packet data from the source to the destination. Therefore, many researchers are eager to design energy efficient routing protocol to minimize energy consumption in UWSNs. As the opportunistic routing (OR) is the most promising method to be used in UWSNs, this paper focuses on the existing proposed energy efficient OR protocol in UWSNs. This paper reviews the existing proposed energy efficient OR protocol, classifying them into 3 categories namely sender-side-based, receiver-side-based and hybrid. Furthermore each of the protocols is reviewed in detail, and its advantages and disadvantages are discussed. Finally, we discuss potential future work research directions in UWSNs, especially for energy efficient OR protocol design

Energy Efficiency

This book is one of the most comprehensive and up-to-date books written on Energy Efficiency. The readers will learn about different technologies for energy efficiency policies and programs to reduce the amount of energy. The book provides some studies and specific sets of policies and programs that are implemented in order to maximize the potential for energy efficiency improvement. It contains unique insights from scientists with academic and industrial expertise in the field of energy efficiency collected in this multi-disciplinary forum

Acoustic signal-based underwater oil leak detection and localization

Underwater Wireless Sensor Networks (UWSNs) have been becoming popular for exploring offshore, natural resource development, geological oceanography, and monitoring the underwater environment. The acoustic channel characteristics in underwater impose challenges, including limited bandwidth, signal attenuation, and propagation delay that limits UWSN utilization. The marine environment is under threat from pollution, which impacts human life and activities. Compared to other pollution types, the oil leak is a significant threat to the marine ecosystem. When the leaked oil or other petroleum products mix with water in the ocean, significant biological and economic impacts could result. Although much research has focused on improving the reception and processing of acoustic signals, increasing performance, and reducing packet delay, no significant research results have been reported on finding an effective early-stage leak detection method using acoustic signal processing. Accurate information about oil spill location and its characteristics is much needed for oil spill containment and cleanup operations. Developing an efficient under- water oil leak detection and localization algorithm is still challenging in UWSNs because of the impairments of the acoustic channel. In this thesis, we propose a technique that detects the presence of an oil leak in the underwater environment at an early stage. We also propose a localization algorithm that determines the approximate location of the oil leak. Firstly, we review the propagation properties of acoustic signals to understand acoustic communication in the marine environment better. We then discuss the transmission of sound in terms of reflection and refraction. We propose a leak detection technique based on the range estimation method to detect oil leak at an early stage before reaching the ocean sur- face. We perform a two-dimensional analysis for evaluating the performance of the proposed detection technique. To investigate the proposed technique, we perform evaluation with different network sizes and topologies. We discuss the detection ratio, network scalability, power and intensity of the received signal. We then perform a three-dimensional analysis to evaluate the performance of the proposed technique. We conduct theoretical analysis to investigate the proposed technique in terms of detection ratio, network scalability, power and intensity of the received signal. We assess the efficiency of the proposed detection method by considering an oil leak at different ocean levels. Finally, we propose a cooperative localization algorithm for localizing the leak in the UWSN. We then evaluate the proposed localization algorithm for two different topologies. Our results show that our proposed technique works well for an underwater network with concentric hexagonal topology. We can extend the proposed method for other types of targets with different shapes and sizes

Underwater Sensor Nodes and Networks

Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field.Lloret, J. (2013). Underwater Sensor Nodes and Networks. Sensors. 13(9):11782-11796. doi:10.3390/s130911782S1178211796139Garcia, M., Sendra, S., Lloret, G., & Lloret, J. (2011). Monitoring and control sensor system for fish feeding in marine fish farms. IET Communications, 5(12), 1682-1690. doi:10.1049/iet-com.2010.0654Martinez, J. J., Myers, J. R., Carlson, T. J., Deng, Z. D., Rohrer, J. S., Caviggia, K. A., … Weiland, M. A. (2011). Design and Implementation of an Underwater Sound Recording Device. Sensors, 11(9), 8519-8535. doi:10.3390/s110908519Ardid, M., Martínez-Mora, J. A., Bou-Cabo, M., Larosa, G., Adrián-Martínez, S., & Llorens, C. D. (2012). Acoustic Transmitters for Underwater Neutrino Telescopes. Sensors, 12(4), 4113-4132. doi:10.3390/s120404113Baronti, F., Fantechi, G., Roncella, R., & Saletti, R. (2012). Wireless Sensor Node for Surface Seawater Density Measurements. Sensors, 12(3), 2954-2968. doi:10.3390/s120302954Mànuel, A., Roset, X., Rio, J. D., Toma, D. M., Carreras, N., Panahi, S. S., … Cadena, J. (2012). Ocean Bottom Seismometer: Design and Test of a Measurement System for Marine Seismology. Sensors, 12(3), 3693-3719. doi:10.3390/s120303693Jollymore, A., Johnson, M. S., & Hawthorne, I. (2012). Submersible UV-Vis Spectroscopy for Quantifying Streamwater Organic Carbon Dynamics: Implementation and Challenges before and after Forest Harvest in a Headwater Stream. Sensors, 12(4), 3798-3813. doi:10.3390/s120403798Won, T.-H., & Park, S.-J. (2012). Design and Implementation of an Omni-Directional Underwater Acoustic Micro-Modem Based on a Low-Power Micro-Controller Unit. Sensors, 12(2), 2309-2323. doi:10.3390/s120202309Sánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2012). An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks. Sensors, 12(6), 6837-6856. doi:10.3390/s120606837Shin, S.-Y., & Park, S.-H. (2011). A Cost Effective Block Framing Scheme for Underwater Communication. Sensors, 11(12), 11717-11735. doi:10.3390/s111211717Kim, Y., & Park, S.-H. (2011). A Query Result Merging Scheme for Providing Energy Efficiency in Underwater Sensor Networks. Sensors, 11(12), 11833-11855. doi:10.3390/s111211833Llor, J., & Malumbres, M. P. (2012). Underwater Wireless Sensor Networks: How Do Acoustic Propagation Models Impact the Performance of Higher-Level Protocols? Sensors, 12(2), 1312-1335. doi:10.3390/s120201312Zhang, G., Hovem, J. M., & Dong, H. (2012). Experimental Assessment of Different Receiver Structures for Underwater Acoustic Communications over Multipath Channels. Sensors, 12(2), 2118-2135. doi:10.3390/s120202118Ramezani, H., & Leus, G. (2012). Ranging in an Underwater Medium with Multiple Isogradient Sound Speed Profile Layers. Sensors, 12(3), 2996-3017. doi:10.3390/s120302996Lloret, J., Sendra, S., Ardid, M., & Rodrigues, J. J. P. C. (2012). Underwater Wireless Sensor Communications in the 2.4 GHz ISM Frequency Band. Sensors, 12(4), 4237-4264. doi:10.3390/s120404237Gao, M., Foh, C. H., & Cai, J. (2012). On the Selection of Transmission Range in Underwater Acoustic Sensor Networks. Sensors, 12(4), 4715-4729. doi:10.3390/s120404715Gómez, J. V., Sandnes, F. E., & Fernández, B. (2012). Sunlight Intensity Based Global Positioning System for Near-Surface Underwater Sensors. Sensors, 12(2), 1930-1949. doi:10.3390/s120201930Han, G., Jiang, J., Shu, L., Xu, Y., & Wang, F. (2012). Localization Algorithms of Underwater Wireless Sensor Networks: A Survey. Sensors, 12(2), 2026-2061. doi:10.3390/s120202026Moradi, M., Rezazadeh, J., & Ismail, A. S. (2012). A Reverse Localization Scheme for Underwater Acoustic Sensor Networks. Sensors, 12(4), 4352-4380. doi:10.3390/s120404352Lee, S., & Kim, K. (2012). Localization with a Mobile Beacon in Underwater Acoustic Sensor Networks. Sensors, 12(5), 5486-5501. doi:10.3390/s120505486Mohamed, N., Jawhar, I., Al-Jaroodi, J., & Zhang, L. (2011). Sensor Network Architectures for Monitoring Underwater Pipelines. Sensors, 11(11), 10738-10764. doi:10.3390/s111110738Macias, E., Suarez, A., Chiti, F., Sacco, A., & Fantacci, R. (2011). A Hierarchical Communication Architecture for Oceanic Surveillance Applications. Sensors, 11(12), 11343-11356. doi:10.3390/s111211343Zhang, S., Yu, J., Zhang, A., Yang, L., & Shu, Y. (2012). Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation. Sensors, 12(1), 373-390. doi:10.3390/s120100373Climent, S., Capella, J. V., Meratnia, N., & Serrano, J. J. (2012). Underwater Sensor Networks: A New Energy Efficient and Robust Architecture. 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Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa