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

被引:24
作者
Rahmani, Amir Masoud [1 ]
Ali, Saqib [2 ]
Yousefpoor, Mohammad Sadegh [3 ]
Yousefpoor, Efat [3 ]
Naqvi, Rizwan Ali [4 ]
Siddique, Kamran [5 ]
Hosseinzadeh, Mehdi [6 ]
机构
[1] Natl Yunlin Univ Sci & Technol, Future Technol Res Ctr, Touliu 64002, Yunlin, Taiwan
[2] Sultan Qaboos Univ, Coll Econ & Polit Sci, Dept Informat Syst, Muscat 123, Oman
[3] Islamic Azad Univ, Dept Comp Engn, Dezful Branch, Dezful 73210, Iran
[4] Sejong Univ, Dept Intelligent Mechatron Engn, Seoul 05006, South Korea
[5] Xiamen Univ Malaysia, Dept Informat & Commun Technol, Sepang 43900, Malaysia
[6] Gachon Univ, Pattern Recognit & Machine Learning Lab, 1342 Seongnamdaero, Seongnam 13120, South Korea
关键词
wireless sensor networks (WSNs); coverage; fuzzy logic; metaheuristic algorithms; Internet of Things (IoT); OPTIMIZATION; INTELLIGENCE;
D O I
10.3390/math9182251
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页数:41
相关论文
共 48 条
[1]   HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks [J].
Baradaran, Amir Abbas ;
Navi, Keivan .
FUZZY SETS AND SYSTEMS, 2020, 389 :114-144
[3]   Optimal barrier coverage for critical area surveillance using wireless sensor networks [J].
Benahmed, Tariq ;
Benahmed, Khelifa .
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2019, 32 (10)
[4]  
Castro L. D., 2002, Artificial Neural Networks in Pattern Recognition, University of Paisley, Kent, Canterbury, United Kingdom, P67
[5]   On Area Coverage Reliability of Mobile Wireless Sensor Networks With Multistate Nodes [J].
Chakraborty, Suparna ;
Goyal, Neeraj Kumar ;
Soh, Sieteng .
IEEE SENSORS JOURNAL, 2020, 20 (09) :4992-5003
[6]   Ant colony optimization -: Artificial ants as a computational intelligence technique [J].
Dorigo, Marco ;
Birattari, Mauro ;
Stuetzle, Thomas .
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2006, 1 (04) :28-39
[7]   Coverage Protocols for Wireless Sensor Networks: Review and Future Directions [J].
Elhabyan, Riham ;
Shi, Wei ;
St-Hilaire, Marc .
JOURNAL OF COMMUNICATIONS AND NETWORKS, 2019, 21 (01) :45-60
[8]   Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization [J].
Eusuff, M ;
Lansey, K ;
Pasha, F .
ENGINEERING OPTIMIZATION, 2006, 38 (02) :129-154
[9]  
Fahmy HMA, 2020, WIRELESS SENSOR NETW, DOI [10.1007/978-3-030-29700-8, DOI 10.1007/978-3-030-29700-8]
[10]   Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey [J].
Farsi, Mohammed ;
Elhosseini, Mostafa A. ;
Badawy, Mahmoud ;
Ali, Hesham Arafat ;
Eldin, Hanaa Zain .
IEEE ACCESS, 2019, 7 :28940-28954