Open Access iconOpen Access

ARTICLE

crossmark

Efficient Heuristic for Optimal MILP-LoRa Adaptive Resource Allocation for Aquaculture

M. Iniyan Arasu1,*, S. Subha Rani1, G. Raswin Geoffery2

1 Department of ECE, PSG College of Technology, Coimbatore, 641004, Tamilnadu, India
2 Dr. Jayalalithaa Fisheries University, Nagapattinam, 611002, Tamilnadu, India

* Corresponding Author: M. Iniyan Arasu. Email: email

Intelligent Automation & Soft Computing 2022, 33(2), 729-742. https://doi.org/10.32604/iasc.2022.021973

Abstract

LoRa is well-known for its extensive communication range, inexpensive efficiency, and reduced or less power consumption in end devices. End-device energy consumption in LoRa networks is ludicrous because some end-devices use massive dissemination variables to reach the remote doorway. Furthermore, the batteries in these end devices deplete very quickly, reducing network life significantly. To address this issue, an optimal mixed-integer linear programming long-range technique (OMILP-LoRa) was used in this study. The primary goal of this research is to enable adaptive resource allocation using the unique OMILP-LoRa protocol. The ACCURATE heuristic and the OMILP model for LoRaWAN resource allocation are presented in this work. The ACCURATE method was used to dynamically modify the spreading factor (SF) and carrier frequency (CF) configurations for every LoRaWAN IoT devices. The results shows the ACCURATE heuristic produces results that are related to the optimal obtained through the OMILP-LoRa device for channel use, increasing the placement of LoRaWAN, steps to prevent collisions, and enhancing the complete system. The suggested method’s performance includes a comparison of the proposed approach to different existing methods, including the ILP, LoRa, and MILP methods.

Keywords


Cite This Article

APA Style
Arasu, M.I., Rani, S.S., Geoffery, G.R. (2022). Efficient heuristic for optimal milp-lora adaptive resource allocation for aquaculture. Intelligent Automation & Soft Computing, 33(2), 729-742. https://doi.org/10.32604/iasc.2022.021973
Vancouver Style
Arasu MI, Rani SS, Geoffery GR. Efficient heuristic for optimal milp-lora adaptive resource allocation for aquaculture. Intell Automat Soft Comput . 2022;33(2):729-742 https://doi.org/10.32604/iasc.2022.021973
IEEE Style
M.I. Arasu, S.S. Rani, and G.R. Geoffery, “Efficient Heuristic for Optimal MILP-LoRa Adaptive Resource Allocation for Aquaculture,” Intell. Automat. Soft Comput. , vol. 33, no. 2, pp. 729-742, 2022. https://doi.org/10.32604/iasc.2022.021973



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1619

    View

  • 1009

    Download

  • 0

    Like

Share Link