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An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks

Author

Listed:
  • Amir Masoud Rahmani

    (Future Technology Research Center, National Yunlin University of Science and Technology, Douliou 64002, Yunlin, Taiwan
    Amir Masoud Rahmani and Rizwan Ali Naqvi have contributed equally to this work.)

  • Saqib Ali

    (Department of Information Systems, College of Economics and Political Science, Sultan Qaboos University, Muscat P.C.123, Oman)

  • Mohammad Sadegh Yousefpoor

    (Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful 73210, Iran)

  • Efat Yousefpoor

    (Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful 73210, Iran)

  • Rizwan Ali Naqvi

    (Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
    Amir Masoud Rahmani and Rizwan Ali Naqvi have contributed equally to this work.)

  • Kamran Siddique

    (Department of Information and Communication Technology, Xiamen University Malaysia, Sepang 43900, Malaysia)

  • Mehdi Hosseinzadeh

    (Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeanggu, Seongnam 13120, Korea)

Abstract

Coverage is a fundamental issue in wireless sensor networks (WSNs). It plays a important role in network efficiency and performance. When sensor nodes are randomly scattered in the network environment, an ON/OFF scheduling mechanism can be designed for these nodes to ensure network coverage and increase the network lifetime. In this paper, we propose an appropriate and optimal area coverage method. The proposed area coverage scheme includes four phases: (1) Calculating the overlap between the sensing ranges of sensor nodes in the network. In this phase, we present a novel, distributed, and efficient method based on the digital matrix so that each sensor node can estimate the overlap between its sensing range and other neighboring nodes. (2) Designing a fuzzy scheduling mechanism. In this phase, an ON/OFF scheduling mechanism is designed using fuzzy logic. In this fuzzy system, if a sensor node has a high energy level, a low distance to the base station, and a low overlap between its sensing range and other neighboring nodes, then this node will be in the ON state for more time. (3) Predicting the node replacement time. In this phase, we seek to provide a suitable method to estimate the death time of sensor nodes and prevent possible holes in the network, and thus the data transmission process is not disturbed. (4) Reconstructing and covering the holes created in the network. In this phase, the goal is to find the best replacement strategy of mobile nodes to maximize the coverage rate and minimize the number of mobile sensor nodes used for covering the hole. For this purpose, we apply the shuffled frog-leaping algorithm (SFLA) and propose an appropriate multi-objective fitness function. To evaluate the performance of the proposed scheme, we simulate it using NS2 simulator and compare our scheme with three methods, including CCM-RL, CCA, and PCLA. The simulation results show that our proposed scheme outperformed the other methods in terms of the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime.

Suggested Citation

  • Amir Masoud Rahmani & Saqib Ali & Mohammad Sadegh Yousefpoor & Efat Yousefpoor & Rizwan Ali Naqvi & Kamran Siddique & Mehdi Hosseinzadeh, 2021. "An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks," Mathematics, MDPI, vol. 9(18), pages 1-41, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2251-:d:634942
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    References listed on IDEAS

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    1. Chakraborty, Suparna & Goyal, N.K. & Mahapatra, S. & Soh, Sieteng, 2020. "A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Weili Wu & Zhao Zhang & Wonjun Lee & Ding-Zhu Du, 2020. "Optimal Coverage in Wireless Sensor Networks," Springer Optimization and Its Applications, Springer, number 978-3-030-52824-9, June.
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    Cited by:

    1. Muhammad Umair Khan & Mehdi Hosseinzadeh & Amir Mosavi, 2022. "An Intersection-Based Routing Scheme Using Q-Learning in Vehicular Ad Hoc Networks for Traffic Management in the Intelligent Transportation System," Mathematics, MDPI, vol. 10(20), pages 1-25, October.
    2. Jan Lansky & Saqib Ali & Amir Masoud Rahmani & Mohammad Sadegh Yousefpoor & Efat Yousefpoor & Faheem Khan & Mehdi Hosseinzadeh, 2022. "Reinforcement Learning-Based Routing Protocols in Flying Ad Hoc Networks (FANET): A Review," Mathematics, MDPI, vol. 10(16), pages 1-60, August.
    3. Amir Masoud Rahmani & Rizwan Ali Naqvi & Efat Yousefpoor & Mohammad Sadegh Yousefpoor & Omed Hassan Ahmed & Mehdi Hosseinzadeh & Kamran Siddique, 2022. "A Q-Learning and Fuzzy Logic-Based Hierarchical Routing Scheme in the Intelligent Transportation System for Smart Cities," Mathematics, MDPI, vol. 10(22), pages 1-31, November.

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