An Efficient Mobile Descend Scheduling for Enterprise of Mobility-Grounded Systems for Wireless Sensor Networks

Authors

  • Srividya B. V. Associate Professor, Department of Electronics and Telecommunication Engineering Dayananda sagar college of Engineering
  • Smitha Sasi Associate Professor, Department of Electronics and Telecommunication Engineering, Dayananda sagar college of Engineering
  • Vinod B. Durdi Associate Professor, Department of Electronics and Telecommunication Engineering Dayananda Sagar College of Engineering
  • Anju V. Kulkarni Professor, Department of Electronics and Telecommunication Engineering Dayananda sagar college of Engineering
  • Vindhya Malagi Department of AI ML Professor Dayananda sagar college of Engineering
  • Radhika Menon Professor Department of Mathematics Dr DyPatil Institute of Technology

Keywords:

WSN, AACO, HHH-SS, CHs

Abstract

One of the main objectives of the WSNs is data collection, where there is a difficult situation between effective information gathering and energy efficacy. Because of the large demand for the relay nodes that are closer to the base station, data routing also has an impact on the hotspot issue. A way to overcome the aforementioned difficulties is by mobile descend -based data collecting. In the beginning, we provide an approach for data collecting utilizing a single portable descend. In order to cover the entire network and reduce end-to-end delay, a new collecting method called K-medoid with amalgam gathering head assortment procedure Hybrid HH-SS (hybrid Harris Hawk and Slap Swarm) optimization method are used. Using the use of the AACO (Adaptive Ant Colony Optimization) process, a path that is ideal for the mobile descend is discovered. The mobile descend uses the best route to gather data and connects to CHs via short-range communications. Descend mobility increases battery-operated device longevity while lowering energy consumption. This research suggests a data collection method for large-scale WSNs based on several mobile descends. In this case, the best set of mobile descends is enough to collect the data packets for network scheduling. By combining the three ideal operations, such as gathering, local, and universal mobile descend trajectory designs, the suggested approach maximizes the network lifetime. A modified gap statistic approach is applied to handpick the paramount set of clusters after first considering a hierarchical clustering mechanism.

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Published

11.07.2023

How to Cite

B. V., S. ., Sasi, S. ., Durdi, V. B. ., Kulkarni, A. V. ., Malagi, V. ., & Menon, R. . (2023). An Efficient Mobile Descend Scheduling for Enterprise of Mobility-Grounded Systems for Wireless Sensor Networks. International Journal of Intelligent Systems and Applications in Engineering, 11(8s), 328–337. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3056

Issue

Vol. 11 No. 8s (2023): Advances on Machine Learning and Artificial Intelligence in Computer Technology

Section

Research Article

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