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A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm

Author

Listed:
  • Baohui Shi

    (School of Computer and Communication, Beijing Information Technology College, Beijing 100101, China)

  • Yuexia Zhang

    (School of Information and Communication Engineering, Beijing Information Science & Technology University, Beijing 100101, China
    Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science & Technology University, Beijing 100101, China)

Abstract

Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the wireless sensor network is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. In this paper, a routing protocol is proposed and simulated based on an ant colony optimization algorithm’s performance. The clustering is performed with a routing method based on energy level criteria, collision reduction, distance from the cluster-head to the destination, and neighborhood energy in the proposed method. The cluster head is selected based on the maximum residual energy, minimum distance with other clusters, and consumed energy. This energy is minimized to reach the base station. The node with more energy than the threshold is selected as the new cluster head. Then, four conditions are applied for routing: the shortest path, the leading path, the shortest distance to the source node and the destination node, and routing. Results show that after about 50 cycles of transferring information, only the average of 19.4% of the initial energy is consumed in the network nodes. Therefore, obtained results illustrate that the proposed method helps to retain the energy more than 40% comparing the available methods.

Suggested Citation

  • Baohui Shi & Yuexia Zhang, 2021. "A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm," Energies, MDPI, vol. 14(6), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1709-:d:520370
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    References listed on IDEAS

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    1. Sang-Hyun Park & Seungryong Cho & Jung-Ryun Lee, 2014. "Energy-Efficient Probabilistic Routing Algorithm for Internet of Things," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, April.
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    Cited by:

    1. Shengbin Liang & Tongtong Jiao & Wencai Du & Shenming Qu, 2021. "An improved ant colony optimization algorithm based on context for tourism route planning," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-16, September.
    2. Rizwan Aslam Butt & Adnan Akhunzada & Muhammad Faheem & Basit Raza, 2022. "Enhanced Energy Savings with Adaptive Watchful Sleep Mode for Next Generation Passive Optical Network," Energies, MDPI, vol. 15(5), pages 1-17, February.
    3. Melinda Timea Fülöp & Miklós Gubán & György Kovács & Mihály Avornicului, 2021. "Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity," Energies, MDPI, vol. 14(10), pages 1-22, May.

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