WSN Data Gathering Using TSP-Modified RNNs and Horse Herd Algorithm
Received: 2 May 2025 | Revised: 15 May 2025 | Accepted: 22 May 2025 | Online: 2 August 2025
Corresponding author: Haider Abdulkarim
Abstract
Efficient data-gathering algorithms ensure efficient operation of Wireless Sensor Networks (WSNs) and prevent data loss. This study proposes the Traveling Salesman Problem (TSP) algorithm to gather WSN data. Two variants of the TSP are proposed and implemented, Recurrent Neural Network (RNN) and Horse Herd Optizations (HHO), using the remaining node energy as a second factor in selecting the shortest data-gathering path in addition to node distance. The simulation results show that TSP based on RNN and the weighted sum of both distance and energy outperforms the classic TSP algorithm, shortening the overall path and maximizing the WSN lifetime.
Keywords:
traveling salesman problem, wireless sensor network, data gathering, recurrent neural network, horse herd optimizationDownloads
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Copyright (c) 2025 Haider Abdulkarim, Marwa K. Farhan, Mustafa Ghanim, Ayman N. Muhi, Mohaimen Q. Algburi
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