Kamal Kumar Gola
ABSTRACT
This paper proposes an Angle Time of the Red Vulture Arrival Approach (ATRVA) to address the propagation speed, latency, and error of mobility of node localization in UWSNs. Time Difference of Arrival (TDOA) is utilized to determine the range of known and unknown nodes. The novel Red Vulture Optimization Algorithm (RVOA) promotes the precise estimation of the node's localization. Additionally, the Euclidean distance strategy combines the window prediction method to decrease estimation error and delay. Consequently, the node mobility model is used to predict each time point of velocity along with position, which allows for the conclusion of underwater location. The proposed approach is analyzed and compared with existing techniques such as Movement Prediction Localization (MPL), Genetic Algorithm -Scalable Localization with Mobility Prediction (GA-SLMP), Scalable Localization with Mobility Prediction (SLMP) and Localization Scheme for Large Scale (LSLS). Thus, the proposed one is superior to others in terms of energy consumption, position error, and location coverage.
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Cross Ref
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Index Terms
- Optimal Localization Prediction Using Red Vulture Arrival Approach in Underwater Sensor Networks
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