Two Fuzzy Virtual Force Algorithms to Improve Sensor Deployment in Wireless Sensor Networks
Subject Areas :
Keywords: Maximal Coverage, Sensor Placement, Virtual Force Algorithm, Fuzzy System,
Abstract :
Maximizing area coverage is an important issue in the placement of wireless network sensors, the realization of which helps to improve the network monitoring power. In many applications, the sensors are first randomly distributed in the sensing filed and then their placement is modified. The virtual force algorithm (VFA) tries to achieve a more desirable deployment from an initial sensing deployment by considering repulsive and attractive forces between the sensors. In this paper, the combination of Takashi-Sugeno fuzzy system with VFA is used to achieve a better redeployment of the sensors. To adaptively adjust optimal distance value of the sensors, two fuzzy methods are proposed in this paper and their role in improving performance of the virtual force algorithm is analyzed. Comparison of the performance of the proposed methods with the state-of-the-art reveals that intelligent and adaptive adjustment of the optimal distance using a fuzzy system leads to higher final coverage ratio over traditional virtual force algorithm (VFA), improved virtual force algorithm (IVFA), fuzzy redeployment algorithm (FRED), and two metaheuristics GA, and PSO. On the other hand, the proposed VF-based methods require much less time to solve the problem than GA and PSO metaheuristic methods.
References:
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D. Kandris, C. Nakas, D. Vomvas, and G. Koulouras, “Applications of Wireless Sensor Networks: An Up-to-Date Survey,” Appl. Syst. Innov., vol. 3, no. 1, 2020, doi: 10.3390/asi3010014.
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A. Boulmaiz, N. Doghmane, S. Harize, N. Kouadria, and D. Messadeg, “Chapter 9 - The use of WSN (wireless sensor network) in the surveillance of endangered bird species,” in Advances in Ubiquitous Computing, A. Neustein, Ed. Academic Press, 2020, pp. 261–306. doi: 10.1016/B978-0-12-816801-1.00009-8.
J.-A. Jiang et al., “A WSN-based automatic monitoring system for the foraging behavior of honey bees and environmental factors of beehives,” Comput. Electron. Agric., vol. 123, pp. 304–318, Apr. 2016, doi: 10.1016/j.compag.2016.03.003.
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A. Ali, Y. K. Jadoon, S. A. Changazi, and M. Qasim, “Military Operations: Wireless Sensor Networks based Applications to Reinforce Future Battlefield Command System,” in 2020 IEEE 23rd International Multitopic Conference (INMIC), Nov. 2020, pp. 1–6. doi: 10.1109/INMIC50486.2020.9318168.
S. M. Mohamed, H. S. Hamza, and I. A. Saroit, “Coverage in mobile wireless sensor networks (M-WSN): A survey,” Comput. Commun., vol. 110, pp. 133–150, Sep. 2017, doi: 10.1016/j.comcom.2017.06.010.
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D. Liang, H. Shen, and L. Chen, “Maximum Target Coverage Problem in Mobile Wireless Sensor Networks,” Sensors, vol. 21, no. 1, p. 184, Dec. 2020, doi: 10.3390/s21010184.
Z. Dong, C. Shang, C.-Y. Chang, and D. S. Roy, “Barrier Coverage Mechanism Using Adaptive Sensing Range for Renewable WSNs,” IEEE Access, vol. 8, pp. 86065–86080, 2020, doi: 10.1109/ACCESS.2020.2992867.
W. Barkhoda and H. Sheikhi, “Immigrant imperialist competitive algorithm to solve the multi-constraint node placement problem in target-based wireless sensor networks,” Ad Hoc Netw., vol. 106, p. 102183, Sep. 2020, doi: 10.1016/j.adhoc.2020.102183.
H. ZainEldin, M. Badawy, M. Elhosseini, H. Arafat, and A. Abraham, “An improved dynamic deployment technique based-on genetic algorithm (IDDT-GA) for maximizing coverage in wireless sensor networks,” J. Ambient Intell. Humaniz. Comput., vol. 11, no. 10, pp. 4177–4194, Oct. 2020, doi: 10.1007/s12652-020-01698-5.
M. Abo-Zahhad, S. M. Ahmed, N. Sabor, and S. Sasaki, “Rearrangement of Mobile Wireless Sensor Nodes for Coverage Maximization Based on Immune Node Deployment Algorithm,” Comput Electr Eng, vol. 43, no. C, pp. 76–89, Apr. 2015, doi: 10.1016/j.compeleceng.2015.04.003.
A. K. Paul and T. Sato, “Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges,” J. Sens. Actuator Netw., vol. 6, no. 4, Art. no. 4, Dec. 2017, doi: 10.3390/jsan6040024.
K. Tarnaris, I. Preka, D. Kandris, and A. Alexandridis, “Coverage and k-Coverage Optimization in Wireless Sensor Networks Using Computational Intelligence Methods: A Comparative Study,” Electronics, vol. 9, no. 4, Art. no. 4, Apr. 2020, doi: 10.3390/electronics9040675.
B. Al-Fuhaidi, A. M. Mohsen, A. Ghazi, and W. M. Yousef, “An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm,” J. Sens., vol. 2020, p. 8818826, Nov. 2020, doi: 10.1155/2020/8818826.
Y. Zou and K. Chakrabarty, “Sensor Deployment and Target Localization in Distributed Sensor Networks,” ACM Trans Embed Comput Syst, vol. 3, no. 1, pp. 61–91, Feb. 2004, doi: 10.1145/972627.972631.
C.-C. Yang and J.-H. Wen, “A Hybrid Local Virtual Force Algorithm for Sensing Deployment in Wireless Sensor Network,” in 2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Jul. 2013, pp. 617–621. doi: 10.1109/IMIS.2013.109.
Y. Li, B. Zhang, and S. Chai, “An energy balanced-virtual force algorithm for Mobile-WSNs,” in 2015 IEEE International Conference on Mechatronics and Automation (ICMA), Aug. 2015, pp. 1779–1784. doi: 10.1109/ICMA.2015.7237755.
X. Deng, Z. Yu, R. Tang, X. Qian, K. Yuan, and S. Liu, “An Optimized Node Deployment Solution Based on a Virtual Spring Force Algorithm for Wireless Sensor Network Applications,” Sensors, vol. 19, no. 8, p. 1817, Apr. 2019, doi: 10.3390/s19081817.
J. Xie, D. Wei, S. Huang, and X. Bu, “A Sensor Deployment Approach Using Improved Virtual Force Algorithm Based on Area Intensity for Multisensor Networks,” Math. Probl. Eng., vol. 2019, p. 8015309, Feb. 2019, doi: 10.1155/2019/8015309.
S. Liu, R. Zhang, and Y. Shi, “Design of coverage algorithm for mobile sensor networks based on virtual molecular force,” Comput. Commun., vol. 150, pp. 269–277, Jan. 2020, doi: 10.1016/j.comcom.2019.11.001.
W. Jun and G. Haoyang, “Virtual force field coverage algorithms for wireless sensor networks in water environments,” Int. J. Sens. Netw., vol. 32, no. 3, pp. 174–181, Jan. 2020, doi: 10.1504/IJSNET.2020.105564.
X. Wang, S. Wang, and D. Bi, “Virtual Force-Directed Particle Swarm Optimization for Dynamic Deployment in Wireless Sensor Networks,” in Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues, Berlin, Heidelberg, 2007, pp. 292–303. doi: 10.1007/978-3-540-74171-8_29.
M. Song, L. Yang, W. Li, and T. A. Gulliver, “Improving wireless sensor network coverage using the VF-BBO algorithm,” in 2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), Aug. 2013, pp. 318–321. doi: 10.1109/PACRIM.2013.6625496.
S. Wang, X. Yang, X. Wang, and Z. Qian, “A Virtual Force Algorithm-Lévy-Embedded Grey Wolf Optimization Algorithm for Wireless Sensor Network Coverage Optimization,” Sensors, vol. 19, no. 12, Art. no. 12, Jan. 2019, doi: 10.3390/s19122735.
M. Li, J. Hu, and X. Cao, “A Two-Phase Coverage Control Algorithm for Self-Orienting Heterogeneous Directional Sensor Networks,” IEEE Access, vol. 8, pp. 88215–88226, 2020, doi: 10.1109/ACCESS.2020.2993554.
X. Qi, Z. Li, C. Chen, and L. Liu, “A wireless sensor node deployment scheme based on embedded virtual force resampling particle swarm optimization algorithm,” Appl. Intell., Sep. 2021, doi: 10.1007/s10489-021-02745-0.
O. Khatib, “Real-Time Obstacle Avoidance for Manipulators and Mobile Robots,” in Autonomous Robot Vehicles, I. J. Cox and G. T. Wilfong, Eds. New York, NY: Springer, 1990, pp. 396–404. doi: 10.1007/978-1-4613-8997-2_29.
L.-X. Wang, A course in fuzzy systems and control. Prentice-Hall, Inc., 1996.
A. Osmani, M. Dehghan, H. Pourakbar, and P. Emdadi, “Fuzzy-Based Movement-Assisted Sensor Deployment Method in Wireless Sensor Networks,” in 2009 First International Conference on Computational Intelligence, Communication Systems and Networks, Jul. 2009, pp. 90–95. doi: 10.1109/CICSYN.2009.97.
D. Izadi, J. Abawajy, and S. Ghanavati, “An Alternative Node Deployment Scheme for WSNs,” IEEE Sens. J., vol. 15, no. 2, pp. 667–675, Feb. 2015, doi: 10.1109/JSEN.2014.2351405.
D. Šoštarić and G. Mester, “Drone localization using ultrasonic TDOA and RSS signal: Integration of the inverse method of a particle filter,” FME Trans., vol. 48, no. 1, pp. 21–30, 2020, doi: 10.5937/fmet2001021S.
