Sensor Coverage Strategy in Underwater Wireless Sensor Networks
Keywords:
Underwater Wireless Sensor Networks(UWSNs), Finite VC-dimension, Gradient direction, Sensor deploymentAbstract
This paper mainly describes studies hydrophone placement strategy in a complex underwater environment model to compute a set of "good" locations where data sampling will be most effective. Throughout this paper it is assumed that a 3-D underwater topographic map of a workspace is given as input.Since the negative gradient direction is the fastest descent direction, we fit a complex underwater terrain to a differentiable function and find the minimum value of the function to determine the low-lying area of the underwater terrain.The hydrophone placement strategy relies on gradient direction algorithm that solves a problem of maximize underwater coverage: Find the maximize coverage set of hydrophone inside a 3-D workspace. After finding the maximize underwater coverage set, to better take into account the optimal solution to the problem of data sampling, the finite VC-dimension algorithm computes a set of hydrophone that satisfies hydroacoustic signal energy loss constraints. We use the principle of the maximize splitting subset of the coverage set and the ”dual” set of the coverage covering set, so as to find the hitting set, and finally find the suboptimal set (i.e., the sensor suboptimal coverage set).Compared with the random deployment algorithm, although the computed set of hydrophone is not guaranteed to have minimum size, the algorithm does compute with high network coverage quality.References
Bartlett, P.L.; Harvey,N.(2019). Nearly-tight vc-dimension and pseudodimension bounds for piecewise linear neural networks. Journal of Machine Learning Research, 20(63), 1-17, 2019.
Binh, H.T.; Hanh, N.T.(2018). Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural computing and applications, 30(7), 2305-2317, 2018. https://doi.org/10.1007/s00521-016-2823-5
Biswas, S.; Das, R.; Chatterjee, P.(2018). Energy-efficient connected target coverage in multi-hop wireless sensor networks. Industry interactive innovations in science, engineering and technology, Springer, 411-421, 2018. https://doi.org/10.1007/978-981-10-3953-9_40
Brönnimann, H.; Goodrich, M.T.(1995). Almost optimal set covers in finite vc-dimension. Discrete & Computational Geometry, 14(4), 463-479, 1995. https://doi.org/10.1007/BF02570718
Bryner, D.; Huffer, F.; Srivastava, A.; Tucker, J.D.(2016) Underwater minefield detection in clutter data using spatial point-process models. IEEE Journal of Oceanic Engineering, 41(3), 670-681, 2016. https://doi.org/10.1109/JOE.2015.2493598
Chan, T.M.(2018). Improved deterministic algorithms for linear programming in low dimensions. ACM Transactions on Algorithms (TALG), 14(3), 30, 2018. https://doi.org/10.1145/3155312
Commuri, S.; Watfa, M.K.(2006). Coverage strategies in wireless sensor networks. International Journal of Distributed Sensor Networks, 2(4), 333-353, 2006. https://doi.org/10.1080/15501320600719151
Darabkh ,K.A; Alsaraireh, N.R.(2018). A yet efficient target tracking algorithm in wireless sensor networks. 2018 15th International Multi-Conference on Systems, Signals & Devices (SSD), IEEE, 7-11, 2018. https://doi.org/10.1109/SSD.2018.8570404
Ducoffe, G.; Habib, M.; Viennot,L.(2019). Diameter computation on h-minor free graphs and graphs of bounded (distance) vc-dimension. arXiv preprint arXiv:1907.04385, 2019. https://doi.org/10.1137/1.9781611975994.117
Harizan, S.; Kuila, P.(2019). Coverage and connectivity aware energy efficient scheduling in target based wireless sensor networks: an improved genetic algorithm based approach. Wireless Networks, 25(4), 1995-2011, 2019. https://doi.org/10.1007/s11276-018-1792-2
Hu, W.; Yao, W.H.; Hu, Y.W.; Li, H.H.(2019). Selection of cluster heads for wireless sensor network in ubiquitous power internet of things. International Journal of Computers Communications & Control, 14(3), 44-358, 2019. https://doi.org/10.15837/ijccc.2019.3.3573
Jagtap, A.M.; Gomathi, N.(2020) Energy efficient sensor deployment with tcov and ncon in wireless sensor networks: Energy efficient sensor deployment with tcov. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 11(1), 1-22, 2020. https://doi.org/10.4018/IJERTCS.2020010101
Kjos-Hanssen, B.; Felix, C.J.; Kim, S.Y.; Lamb, E.; Takahashi, D.(2020). Vc-dimensions of nondeterministic finite automata for words of equal length. arXiv preprint arXiv:2001.02309, 2020.
Lacharité, M.; Brown, C.J.; Gazzola, V.(2018). Multisource multibeam backscatter data: developing a strategy for the production of benthic habitat maps using semi-automated seafloor classification methods. Marine Geophysical Research, 39(1-2), 307-322, 2018. https://doi.org/10.1007/s11001-017-9331-6
Luo, X.B.; Xu, D.M.; Hu, J.J.; Hu, M.(2014). Application research of 3d imaging sonar system in salvage process. Applied Mechanics and Materials, Trans Tech Publ, 643, 279-282, 2014. https://doi.org/10.4028/www.scientific.net/AMM.643.279
Morozs, N.; Mitchell, P.D.; Zakharov, Y.; Mourya, R.(2018). Robust tda-mac for practical underwater sensor network deployment: Lessons from usmart sea trials. Proceedings of the Thirteenth ACM International Conference on Underwater Networks & Systems, ACM, 11, 2018. https://doi.org/10.1145/3291940.3291970
Mridula, K.M.; Ameer, P.M.(2018). Three-dimensional sensor network connectivity considering border effects and channel randomness with application to underwater networks. IET Communications, 12(8), 94-1002, 2018. https://doi.org/10.1049/iet-com.2017.0952
Nazarzehi, V.; Savkin, A.V.(2018). Distributed self-deployment of mobile wireless 3d robotic sensor networks for complete sensing coverage and forming specific shapes. Robotica, 36(1), 1-18, 2018. https://doi.org/10.1017/S0263574717000121
Nielsen, P.L.; Muzi, L.; Siderius, M.(2017). Seabed characterization from ambient noise using short arrays and autonomous vehicles. IEEE Journal of Oceanic Engineering, 42(4), 1094-1101, 2017. https://doi.org/10.1109/JOE.2017.2712338
Ojha, T.; Misra, S.; Raghuwanshi, S.(2015). Wireless sensor networks for agriculture: The stateof- the-art in practice and future challenges. Computers and Electronics in Agriculture, 118, 66-84, 2015. https://doi.org/10.1016/j.compag.2015.08.011
Osamy, W.; Khedr, A.M.(2018). An algorithm for enhancing coverage and network lifetime in cluster-based wireless sensor networks. International Journal of Communication Networks and Information Security, 10(1), 1-9, 2018.
Pinto, L.; Gopalan, D.(2019). Limiting network size within finite bounds for optimization. arXiv preprint arXiv:1903.02809, 2019.
Poduri, S.; Pattem, S.; Krishnamachari, B.; Sukhatme, G.(2006). Sensor network configuration and the curse of dimensionality. Proc. Third Workshop on Embedded Networked Sensors (EmNets 2006), Cambridge, MA, USA. Citeseer, 2006.
Saffran, J.R.; Kirkham, N.Z.(2018). Infant statistical learning. Annual review of psychology, 69, 2018. https://doi.org/10.1146/annurev-psych-122216-011805
Saikia, M.; Hussain, M.A.(2019). Wireless sensor node deployment strategy for hilly terrains-a surface approximation based approach. IET Wireless Sensor Systems, 9(5), 284-294, 2019. https://doi.org/10.1049/iet-wss.2018.5095
Shakkottai, S.; Srikant, R.; Shroff, N.B.(2005). Unreliable sensor grids: Coverage, connectivity and diameter. Ad Hoc Networks, 3(6), 702-716, 2005. https://doi.org/10.1016/j.adhoc.2004.02.001
Tam, N.T.; Hai, D.T.(2018). Improving lifetime and network connections of 3d wireless sensor networks based on fuzzy clustering and particle swarm optimization. Wireless Networks, 24(5), 1477-1490, 2018. https://doi.org/10.1007/s11276-016-1412-y
Yao, L.; Du, X.J.(2020). Identification of underwater targets based on sparse representation. IEEE Access, 8, 215-228, 2020. https://doi.org/10.1109/ACCESS.2019.2962005
Zhang, C.L.; Bai,X.L.; Teng,J.(2010). Constructing low-connectivity and full-coverage three dimensional sensor networks. IEEE Journal on Selected Areas in Communications, 28(7), 984-993, 2010. https://doi.org/10.1109/JSAC.2010.100903
Zheng, X.; Feng, C.; Li, T.Y.(2019). Analysis of autonomous underwater vehicle (auv) navigational states based on complex networks. Ocean Engineering, 187, 106141, 2019. https://doi.org/10.1016/j.oceaneng.2019.106141
Zou, Y.; Chakrabarty, K.(2003). Sensor deployment and target localization based on virtual forces. IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No. 03CH37428), IEEE, 2, 1293-1303, 2003. https://doi.org/10.1109/INFCOM.2003.1208965
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