Optimum frequency selection for localization of underwater AUV using dynamic positioning parameters

Underwater connectivity has been a leading field of study in undersea navigation, deep-sea investigation and autonomous underwater vehicle control (AUVs). Because of the low attenuation (signal reduction) of sound in water, acoustic communication is the most versatile and broadly used tool in underwater network. Factors such as long propagation delay, restricted usable bandwidth, large Doppler range, time-varying channel conditions, pressure and various salinity conditions make the application of the underwater acoustic communication (UWAC) system difficult. Underwater naval monitoring and underwater exploration are the basic uses of Underwater Wireless Sensor Networks (UWSN). The outline of sensor networks has been resurrected into a new age of global physical object tracking with the latest advancement of innovation. This advances in design paved the way for new unopened insider information to be revealed in the area of underwater ecosystems, deep water conditions and discovery of ice sheets. This work provides a proficient packet transmitting technique in a selective frequency to increase the coverage, synchronisation and connectivity between sensor AUVs that are under secluded ocean contour observation. The theoretical model is used to represent the complex dynamics in the sea. Taking into account all the channel properties below the sea, the channel model was created. The AUVs are connected to a cluster-based network and the 3-D location of the AUVs is transmitted using an appropriate depth-based cluster-based routing protocol (DB-CBRP). Through choosing the optimal frequency for the transmission of routing packets, the network's total life is extended with the least delay in routing. As a result of its strength against overly reduced transmission capability and recurrence reuse, the CBRP approach is used to restrict channel impairments. The simulation results of the proposed algorithm reveal that the surveillance AUVs have greater communication, coverage and share their position with each other.

[1]  Weijia Jia,et al.  Constructing low-connectivity and full-coverage three dimensional sensor networks , 2010, IEEE Journal on Selected Areas in Communications.

[2]  Fang Zhu,et al.  An Energy Efficient Routing Protocol Based on Layers and Unequal Clusters in Underwater Wireless Sensor Networks , 2018, J. Sensors.

[3]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[4]  J. Martin Leo Manickam,et al.  Cluster-Based MAC Protocol for Collision Avoidance and TDMA Scheduling in Underwater Wireless Sensor Networks , 2016, Comput. J..

[5]  Chao Yang,et al.  A High-Precision Control Scheme Based on Active Disturbance Rejection Control for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications , 2018, J. Sensors.

[6]  R. Logeshwaran,et al.  Performance analysis of cluster head selection routing protocol in underwater acoustic wireless sensor network , 2015, 2015 2nd International Conference on Electronics and Communication Systems (ICECS).

[7]  Jie Zhang,et al.  Cellular Clustering-Based Interference-Aware Data Transmission Protocol for Underwater Acoustic Sensor Networks , 2020, IEEE Transactions on Vehicular Technology.

[8]  Jingli Du,et al.  Error beacon filtering algorithm based on K-means clustering for underwater Wireless Sensor Networks , 2016, 2016 8th IEEE International Conference on Communication Software and Networks (ICCSN).

[9]  Mazleena Salleh,et al.  Routing protocols based on protocol operations for underwater wireless sensor network: A survey , 2017 .

[10]  Ye Liu,et al.  Topology control models and solutions for signal irregularity in mobile underwater wireless sensor networks , 2015, J. Netw. Comput. Appl..

[11]  Changxing Pei,et al.  A Cross-Layer Protocol for Event-Driven Wireless Sensor Networks , 2009, 2009 First International Conference on Information Science and Engineering.

[12]  Seung-Hyun Oh,et al.  A Data Aggregation Based Efficient Clustering Scheme in Underwater Wireless Sensor Networks , 2014 .

[13]  Ye Liu,et al.  A Complex Network Approach to Topology Control Problem in Underwater Acoustic Sensor Networks , 2014, IEEE Transactions on Parallel and Distributed Systems.

[14]  Qinghai Gao,et al.  Improving probabilistic coverage and connectivity in wireless sensor networks: Cooperation and mobility , 2010, 2010 International Conference on Wireless Communications & Signal Processing (WCSP).

[15]  Debashis De,et al.  CUWSN: energy efficient routing protocol selection for cluster based underwater wireless sensor network , 2019, Microsystem Technologies.

[16]  Mayank Dave,et al.  Protocol Stack of Underwater Wireless Sensor Network: Classical Approaches and New Trends , 2018, Wireless Personal Communications.

[17]  Sudip Misra,et al.  MobiL: A 3-dimensional localization scheme for Mobile Underwater Sensor Networks , 2013, 2013 National Conference on Communications (NCC).

[18]  Anand Nayyar,et al.  Analysis of Simulation Tools for Underwater Sensor Networks (UWSNs) , 2018, International Conference on Innovative Computing and Communications.

[19]  Neeraj Kumar,et al.  A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks , 2013, J. Netw. Comput. Appl..

[20]  Helen M. Wood,et al.  Foreword to the First Issue of the Transactions on Parallel and Distributed Systems , 1990, IEEE Trans. Parallel Distributed Syst..

[21]  Linfeng Liu,et al.  A Deployment Algorithm for Underwater Sensor Networks in Ocean Environment , 2011, J. Circuits Syst. Comput..

[22]  Milica Stojanovic,et al.  Underwater Acoustic Communications and Networking: Recent Advances and Future Challenges , 2008 .