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    Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks

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    [EN] In underwater acoustic modem design, pure asynchrony can contribute to improved wake-up coordination, thus avoiding energy-inefficient synchronization mechanisms. Nodes are designed with a pre-receptor and an acoustically adapted Radio Frequency Identification system, which wakes up the node when it receives an external tone. The facts that no synchronism protocol is necessary and that the time between waking up and packet reception is narrow make pure asynchronism highly efficient for energy saving. However, handshaking in the Medium Control Access layer must be adapted to maintain the premise of pure asynchronism. This paper explores different models to carry out this type of adaptation, comparing them via simulation in ns-3. Moreover, because energy saving is highly important to data gathering driven by underwater vehicles, where nodes can spend long periods without connection, this paper is focused on multi-hop topologies. When a vehicle appears in a 3D scenario, it is expected to gather as much information as possible in the minimum amount of time. Vehicle appearance is the event that triggers the gathering process, not only from the nearest nodes but from every node in the 3D volume. Therefore, this paper assumes, as a requirement, a topology of at least three hops. The results show that classic handshaking will perform better than tone reservation because hidden nodes annulate the positive effect of channel reservation. However, in highly dense networks, a combination model with polling will shorten the gathering time.Blanc Clavero, S. (2020). Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks. Sensors. 20(5):1-16. https://doi.org/10.3390/s20051407S116205Roy, A., & Sarma, N. (2018). Effects of Various Factors on Performance of MAC Protocols for Underwater Wireless Sensor Networks. Materials Today: Proceedings, 5(1), 2263-2274. doi:10.1016/j.matpr.2017.09.228Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges. Wireless Communications and Mobile Computing, 2019, 1-20. doi:10.1155/2019/6470359Rudnick, D. L., Davis, R. E., Eriksen, C. C., Fratantoni, D. M., & Perry, M. J. (2004). Underwater Gliders for Ocean Research. Marine Technology Society Journal, 38(2), 73-84. doi:10.4031/002533204787522703Petritoli, E., & Leccese, F. (2018). High Accuracy Attitude and Navigation System for an Autonomous Underwater Vehicle (AUV). ACTA IMEKO, 7(2), 3. doi:10.21014/acta_imeko.v7i2.535Nam, H. (2018). Data-Gathering Protocol-Based AUV Path-Planning for Long-Duration Cooperation in Underwater Acoustic Sensor Networks. IEEE Sensors Journal, 18(21), 8902-8912. doi:10.1109/jsen.2018.2866837Sun, J., Hu, F., Jin, W., Wang, J., Wang, X., Luo, Y., … Zhang, A. (2020). Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences. Sensors, 20(3), 893. doi:10.3390/s20030893Wahid, A., Lee, S., Kim, D., & Lim, K.-S. (2014). MRP: A Localization-Free Multi-Layered Routing Protocol for Underwater Wireless Sensor Networks. Wireless Personal Communications, 77(4), 2997-3012. doi:10.1007/s11277-014-1690-6Sánchez, 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/s120606837Li, S., Qu, W., Liu, C., Qiu, T., & Zhao, Z. (2019). Survey on high reliability wireless communication for underwater sensor networks. Journal of Network and Computer Applications, 148, 102446. doi:10.1016/j.jnca.2019.102446Jiang, S. (2018). State-of-the-Art Medium Access Control (MAC) Protocols for Underwater Acoustic Networks: A Survey Based on a MAC Reference Model. IEEE Communications Surveys & Tutorials, 20(1), 96-131. doi:10.1109/comst.2017.2768802Chirdchoo, N., Soh, W., & Chua, K. C. (2008). RIPT: A Receiver-Initiated Reservation-Based Protocol for Underwater Acoustic Networks. IEEE Journal on Selected Areas in Communications, 26(9), 1744-1753. doi:10.1109/jsac.2008.081213Zenia, N. Z., Aseeri, M., Ahmed, M. R., Chowdhury, Z. I., & Shamim Kaiser, M. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computer Applications, 71, 72-85. doi:10.1016/j.jnca.2016.06.005Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. (2017). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061-2075. doi:10.1007/s11276-017-1461-xSánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2015). An Acoustic Modem Featuring a Multi-Receiver and Ultra-Low Power. Circuits and Systems, 06(01), 1-12. doi:10.4236/cs.2015.6100

    Adaptive link-weight routing protocol using cross-layer communication for MANET

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    Routing efficiency is one of the challenges offered by Mobile Ad-hoc Networks (MANETs). This paper proposes a novel routing technique called Adaptive Link-Weight (ALW) routing protocol. ALW adaptively selects an optimum route on the basis of available bandwidth, low delay and long route lifetime. The technique adapts a cross-layer framework where the ALW is integrated with application and physical layer. The proposed design allows applications to convey preferences to the ALW protocol to override the default path selection mechanism. The results confirm improvement over AODV in terms of network load, route discovery time and link reliability

    NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks

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    With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)
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