IoT-Enabled Energy-efficient Multipath Power Control for Underwater
Sensor Networks

Pundru Chandra      Shaker Reddy; Yadala      Sucharitha

doi:10.2174/2210327912666220615103257

Abstract

Aims & Background: Energy saving or accurate information transmission within resource limits are the major challenges for IoT Underwater Sensing Networks (IoT-UWSNs) on the Internet. Conventional transfer methods increase the cost of communications, leading to bottlenecks or compromising the reliability of information supply. Several routing techniques were suggested using UWSN to ensure uniform transmission of information or reduce communication latency while preserving a data battery (to avoid an empty hole in the network).

Objectives and Methodology: In this article, adaptable power networking methods based on the Fastest Route Fist (FRF) method and a smaller amount of the business unit method are presented to solve the problems mentioned above. Both Back Laminated Inter Energy Management One (FLMPC-One) networking method, that employs 2-hop neighborhood knowledge, with the Laminated Inter Energy Management Two (FLMPC-Two) networking procedure, which employs 3-hop neighborhood data, were combined to create such innovative technologies (to shortest path selection). Variable Session Portion (SP) and Information Speed (IS) were also considered to ensure that the suggested method is flexible.

Results and Conclusion: These findings show that the suggested methods Shortest Path First without 3-hop Relatives Data (SPF-Three) or Broadness Initial Searching for Shortest Route and Breadth First Search to 3-hop Relatives Data (BFS-Three) successfully developed (BFS-SPF-Three). These suggested methods are successful in respect of minimal Electric Cost (EC) and Reduced Transmission Drop Rates (RTDR) given a small number of operational sites at a reasonable latency, according to the simulated findings.

Keywords: Underwater Sensor network, electric cost, reduced transmission drop rates, information speed, laminated inter energy management, maritime information

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[1]
Narla VL, Kachhoria R, Arun M, Haldorai A, Vijendra Babu D, Jos BM. IoT based energy efficient multipath power control for underwater sensor network. Inter J Syst Assur Eng Manag  2022; 1-10.
 [http://dx.doi.org/10.1007/s13198-021-01560-7]

[2]
Butt SA, Bakar KA, Javaid N, et al. Exploiting layered multi-path routing protocols to avoid void hole regions for reliable data delivery and efficient energy management for IoT-enabled underwater WSNs. Sensors (Basel)  2019; 19(3): 510.
 [http://dx.doi.org/10.3390/s19030510] [PMID: 30691141]

[3]
Awan KM, Shah PA, Iqbal K, Gillani S, Ahmad W, Nam Y. Underwater wireless sensor networks: A review of recent issues and challenges. Wirel Commun Mob Comput  2019; 2019: 2019.
 [http://dx.doi.org/10.1155/2019/6470359]

[4]
Fattah S, Gani A, Ahmedy I, Idris MYI, Targio Hashem IA. A survey on underwater wireless sensor networks: Requirements, taxonomy, recent Advances, and open research challenges. Sensors (Basel)  2020; 20(18): 5393.
 [http://dx.doi.org/10.3390/s20185393] [PMID: 32967124]

[5]
Abbasian Dehkordi S, Farajzadeh K, Rezazadeh J, Farahbakhsh R, Sandrasegaran K, Abbasian Dehkordi M. A survey on data aggregation techniques in IoT sensor networks. Wirel Netw  2020; 26(2): 1243-63.
 [http://dx.doi.org/10.1007/s11276-019-02142-z]

[6]
Gupta O, Goyal N, Anand D, Kadry S, Nam Y, Singh A. Underwater networked wireless sensor data collection for computational intelligence techniques: Issues, challenges, and approaches. IEEE Access  2020; 8: 122959-74.
 [http://dx.doi.org/10.1109/ACCESS.2020.3007502] [PMID: 34192112]

[7]
Jan S, Yafi E, Hafeez A, et al. Investigating master-slave architecture for underwater wireless sensor network. Sensors (Basel)  2021; 21(9): 3000.
 [http://dx.doi.org/10.3390/s21093000] [PMID: 33922886]

[8]
Khan ZA, Karim OA, Abbas S, Javaid N, Zikria YB, Tariq U. Q-learning based energy-efficient and void avoidance routing protocol for underwater acoustic sensor networks. Comput Netw  2021; 197: 108309.
 [http://dx.doi.org/10.1016/j.comnet.2021.108309]

[9]
Kapileswar N, Phani Kumar P. Energy efficient routing in IOT based UWSN using bald eagle search algorithm. Trans Emerg Telecommun Technol  2022; 33(1): e4399.
 [http://dx.doi.org/10.1002/ett.4399]

[10]
Ismail AS, Wang X, Hawbani A, Alsamhi S, Abdel Aziz S. Routing protocols classification for underwater wireless sensor networks based on localization and mobility. Wirel Netw  2022; 28(2): 1-30.
 [http://dx.doi.org/10.1007/s11276-021-02880-z]

[11]
Rizvi HH, Khan SA, Enam RN. Clustering base energy efficient mechanism for an underwater wireless sensor network. Wirel Pers Commun 2022.
 [http://dx.doi.org/10.1007/s11277-022-09536-x]

[12]
Goyal N, Dave M, Verma AK. SAPDA: Secure authentication with protected data aggregation scheme for improving QoS in scalable and survivable UWSNs. Wirel Pers Commun  2020; 113(1): 1-5.
 [http://dx.doi.org/10.1007/s11277-020-07175-8]

[13]
Shaker Reddy PC, Sureshbabu A. An enhanced multiple linear regression model for seasonal rainfall prediction. Int J Sensors Wirel Commun Control  2020; 10(4): 473-83.
 [http://dx.doi.org/10.2174/2210327910666191218124350]

[14]
Courville SW, Sava PC. Speckle noise attenuation in orbital laser vibrometer seismology. Acta Astronaut  2020; 172: 16-32.
 [http://dx.doi.org/10.1016/j.actaastro.2020.03.016]

[15]
Khisa S, Moh S. Survey on recent advancements in energy-efficient routing protocols for underwater wireless sensor networks. IEEE Access  2021; 9: 55045-62.
 [http://dx.doi.org/10.1109/ACCESS.2021.3071490]

[16]
Reddy PCS, Yadala S, Goddumarri SN. Development of rainfall forecasting model using machine learning with singular spectrum analysis. IIUM Eng J  2022; 23(1): 172-86.
 [http://dx.doi.org/10.31436/iiumej.v23i1.1822]

[17]
Awais M, Ali I, Alghamdi TA, et al. Towards void hole alleviation: Enhanced geographic and opportunistic routing protocols in harsh underwater WSNS. IEEE Access  2020; 8: 96592-605.
 [http://dx.doi.org/10.1109/ACCESS.2020.2996367]

[18]
Mhemed R, Comeau F, Phillips W, Aslam N. Void avoidance opportunistic routing protocol for underwater wireless sensor networks. Sensors (Basel)  2021; 21(6): 1942.
 [http://dx.doi.org/10.3390/s21061942] [PMID: 33801951]

[19]
John S, Menon VG, Nayyar A. Simulation-based performance analysis of location-based opportunistic routing protocols in underwater sensor networks having communication voids.In: Data Management, Analytics and Innovation.  Singapore: Springer 2020; pp. 697-711.

[20]
Phung A. A comparison of biogeochemical argo sensors, remote sensing systems, and shipborne field fluorometers to measure chlorophyll a concentrations in the pacific ocean off the northern coast of New Zealand.In: Global Oceans.  Singapore–US Gulf Coast 2020; pp. 1-7.

[21]
Reddy PC, Pradeepa M, Venkatakiran S, Walia R, Saravanan M. Image and signal processing in the underwater environment. J NuclEneSci Power Generat Technol  2021; 10.

[22]
Anand JV, Sundeep K, Rao ND. Underwater sensor protocol for time synchronization and data transmissions using the prediction model. 2020 International Conference on Inventive Computation Technologies (ICICT).  pp. 762-6.
 [http://dx.doi.org/10.1109/ICICT48043.2020.9112388]

[23]
Bhandari KS, Cho GH. Resource oriented topology construction to ensure high reliability in IoT based smart city networks. Inter J SystAssur Eng Manag  2020; 11(4): 798-805.
 [http://dx.doi.org/10.1007/s13198-019-00861-2]

[24]
Buvana M, Loheswaran K, Karanam M, Sivakumar P, Aradhana B, Jayavadivel R. Improved Resource management and utilization based on a fog-cloud computing system with IoT incorporated with Classifier systems. Microprocess Microsyst 2021. Available from: sciencedirect.com/science/article/abs/pii/S0141933120309601

[25]
Khan RA, Xin Q, Roshan N. RK-energy efficient routing protocol for wireless body area sensor networks. Wirel Pers Commun  2021; 116(1): 709-21.
 [http://dx.doi.org/10.1007/s11277-020-07734-z]

[26]
Venkata PM, Karnan B, Latchoumi TP. PLA-Cu reinforced composite filament: Preparation and flexural property printed at different machining conditions. Adv Composite Mater 2021. Available from:
 [http://dx.doi.org/10.1080/09243046.2021.1918608]

[27]
Khan A, Ali I, Ghani A, et al. Routing protocols for underwater wireless sensor networks: Taxonomy, research challenges, routing strategies and future directions. Sensors (Basel)  2018; 18(5): 1619.
 [http://dx.doi.org/10.3390/s18051619] [PMID: 29783686]

[28]
Suresh P, Saravanakumar U, Iwendi C, Mohan S, Srivastava G. Field-programmable gate arrays in a low power vision system. Comput Electr Eng  2021; 90: 106996.
 [http://dx.doi.org/10.1016/j.compeleceng.2021.106996]

[29]
Hemalatha P, Dhanalakshmi K. Cellular automata based energy efficient approach for improving security in IOT. Intell Autom Soft Comput  2022; 32(2): 811-25.
 [http://dx.doi.org/10.32604/iasc.2022.020973]

[30]
Thangamani M, Ganthimathi M, Sridhar SR, Akila M, Keerthana R, Ramesh PS. Detecting coronavirus contact using internet of things. Int J Pervas Comput Commun  2020; 16(5): 447-56.

[31]
Chen Z, Zhou W, Wu S, Cheng L. An on demand load balancing multi-path routing protocol for differentiated services in MWSN. Comput Commun  2021; 179: 296-306.
 [http://dx.doi.org/10.1016/j.comcom.2021.08.020]

[32]
An H, Na Y, Lee H, Perrig A. Resilience evaluation of multi-path routing against network attacks and failures. Electronics (Basel)  2021; 10(11): 1240.
 [http://dx.doi.org/10.3390/electronics10111240]

[33]
Yu CM, Ku ML, Wang LC. BMRHTA: Balanced multi-path routing and hybrid transmission approach for lifecycle maximization in WSNs. IEEE Internet Things J  2021; 9(1): 728-42.

[34]
Luo J, Chen Y, Wu M, Yang Y. A survey of routing protocols for underwater wireless sensor networks. IEEE Comm Surv Tutor  2021; 23(1): 137-60.
 [http://dx.doi.org/10.1109/COMST.2020.3048190]

[35]
Fuada N, Purwoko S. Children under-five health transition information system International Proceedings The 2nd ISMoHIM 2020. Available from: file:///C:/Users/IT-ITS-047/Downloads/194-383-1-SM.pdf

[36]
Shi G, Liu K, Zeng J. Cooperative depth rotation to avoid energy hole for 3D underwater sensor networks. 2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD).  pp. 825-30.

[37]
Lei L, Hao Z, Xu W. Research on scattered point cloud coordinate reduction and hole repair technology based on big data model.  In: International Conference on Big Data and Security; Singapore: Springer. 2020; pp. 420-32.

[38]
Khasawneh AM, Kaiwartya O, Abualigah LM, Lloret J. Green computing in underwater wireless sensor networks pressure centric energy modeling. IEEE Syst J  2020; 14(4): 4735-45.
 [http://dx.doi.org/10.1109/JSYST.2020.2996421]

[39]
Reddy PC, Nachiyappan S, Ramakrishna V, Senthil R. Hybrid model using scrum methodology for software development system. J NuclEneSci Power Generat Techno 2021.

[40]
Draz U, Ali A, Bilal M, et al. Energy efficient proactive routing scheme for enabling reliable communication in underwater internet of things. IEEE Trans Netw Sci Eng  2021; 8(4): 2934-45.
 [http://dx.doi.org/10.1109/TNSE.2021.3109421]

[41]
Baranidharan V, Moulieshwaran B, Karthik V, Sanjay R, Thangabalaji V. Enhanced goodput and energy-efficient geo-opportunistic routing protocol for underwater wireless sensor networks.In: Smart Computing Techniques and Applications.  Singapore: Springer 2021; pp. 585-93.

[42]
Sucharitha Y, Vijayalata Y, Prasad VK. Predicting election results from twitter using machine learning algorithms. Recent Adv Comput Sci Commun  2021; 14(1): 246-56.
 [http://dx.doi.org/10.2174/2666255813999200729164142]

[43]
Mittal N. ZEEHC: Zone-based energy efficient hierarchal clustering hierarchy for wireless sensor networks. Turkish J Comput Math Educ  2021; 12(2): 3003-17. [TURCOMAT].
 [http://dx.doi.org/10.17762/turcomat.v12i2.2340]

[44]
Bai G, Meng Y, Gu Q, Gan X, Li K. Influence of preview distance on lmpc-based path tracking. 2020 39th Chinese Control Conference (CCC) pp.  2363-7.

[45]
Yin X, Zhao X. Data driven learning model predictive control of offshore wind farms. Int J Electr Power Energy Syst  2021; 127: 106639.
 [http://dx.doi.org/10.1016/j.ijepes.2020.106639]

[46]
Baydoun S, Fouvry S. An experimental investigation of adhesive wear extension in fretting interface: application of the contact oxygenation concept. Tribol Int  2020; 147: 106266.
 [http://dx.doi.org/10.1016/j.triboint.2020.106266]

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DOI https://dx.doi.org/10.2174/2210327912666220615103257	Print ISSN 2210-3279
Publisher Name Bentham Science Publisher	Online ISSN 2210-3287

International Journal of Sensors, Wireless Communications and Control

IoT-Enabled Energy-efficient Multipath Power Control for Underwater Sensor Networks

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