Wireless sensor networks (WSNs) displays an encouraging outcome for forest fire (FF) identification. The most serious WSN investigation tasks is forest fire’s early prediction, which is used to save the ecosystem. For conveying the detected information to the BS (base station), the SNs (sensor nodes) are placed in remote forest region in WSN based FF discovery scheme that is manageable by the forest sector. Various studies have been finished in this field but they studied only few amount of constraints and the encountered situations influence has not discussed after the system positioning. In this work, fuzzy based unequal clustering and context aware routing (CAR) procedure with GSO (glow-worm swarm optimization) is developed in RWP (random way point) based dynamic WSNs. Based on FL (fuzzy logic) the unequal clustering is formed and the optimal CH (cluster head) is nominated to convey the information from CM (cluster member) to BS to increase the system lifespan and to decrease the energy consumption. Further, the routing process is performed by the CAR procedure with GSO process to enhance the efficiency of network. Lastly, a case study of FF identification is offered as a justification of the suggested method. The suggested work is executed in MATLAB. The simulation outcomes proved that the proposed approach provide the better outcomes in average energy consumption (0.025 J), PDR (99.4%), jitter (4.01 s), delay (0.0304 s), BER (15%), throughput (144.6Kbps), network lifetime (38.7 s) as related to other current protocols.
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Sinde, R., Begum, F., Njau, K., & Kaijage, S. (2020). Refining network lifetime of wireless sensor network using energy-efficient clustering and DRL-based sleep scheduling. Sensors, 20(5), 1540.
Saranraj, G., Selvamani, K., & Kanagachidambaresan, G. R. (2019). Optimal energy-efficient cluster head selection (OEECHS) for wireless sensor network. Journal of the Institution of Engineers (India) Series B, 100(4), 349–356.
Balaji, S., Julie, E. G., & Robinson, Y. H. (2019). Development of fuzzy based energy efficient cluster routing protocol to increase the lifetime of wireless sensor networks. Mobile Networks and Applications, 24(2), 394–406.
Selvi, M., Thangaramya, K., Ganapathy, S., Kulothungan, K., Nehemiah, H. K., & Kannan, A. (2019). An energy aware trust based secure routing algorithm for effective communication in wireless sensor networks. Wireless Personal Communications, 105(4), 1475–1490.
Kalidoss, T., Rajasekaran, L., Kanagasabai, K., Sannasi, G., & Kannan, A. (2020). QoS aware trust based routing algorithm for wireless sensor networks. Wireless Personal Communications, 110(4), 1637–1658.
Jayarajan, P., Kanagachidambaresan, G. R., Sundararajan, T. V. P., Sakthipandi, K., Maheswar, R., & Karthikeyan, A. (2020). An energy-aware buffer management (EABM) routing protocol for WSN. The Journal of Supercomputing, 76(6), 4543–4555.
Haseeb, K., Almustafa, K. M., Jan, Z., Saba, T., & Tariq, U. (2020). Secure and energy-aware heuristic routing protocol for wireless sensor network. IEEE Access, 8, 163962–163974.
Vinodhini, R., & Gomathy, C. (2020). MOMHR: a dynamic multi-hop routing protocol for WSN using heuristic based multi-objective function. Wireless Personal Communications, 111(2), 883–907.
Shyjith, M.B., Maheswaran, C.P., & Reshma, V.K. (2020). Optimized and Dynamic Selection of Cluster Head Using Energy Efficient Routing Protocol in WSN. Wireless Personal Communications, 1–23.
Radhika, M., & Sivakumar, P. (2020). Energy optimized micro genetic algorithm based LEACH protocol for WSN. Wireless Networks, 1–14.
Moussa, N., El Alaoui, A. E. B., & Chaudet, C. (2020). A novel approach of WSN routing protocols comparison for forest fire detection. Wireless Networks, 26(3), 1857–1867.
AL-Dhief, F. T., Sabri, N., Fouad, S., Latiff, N. M. A., & Albader, M. A. A. (2019). A review of forest fire surveillance technologies: Mobile ad-hoc network routing protocols perspective. Journal of King Saud University-Computer and Information Sciences, 31(2), 135–146.
Al-Dhief, F.T., Latiff, N.M.A., Abd Malik, N.N.N., Sabri, N., Albadr, M.A.A., & Jawad, M.M. (2019). Power Consumption Efficient Routing Protocol for Forest Fire Detection based on Mobile Sensor Networks. In 2019 IEEE 14th Malaysia International Conference on Communication (MICC), (pp. 7–12).
Sinha, D., Kumari, R., & Tripathi, S. (2019). Semisupervised classification based clustering approach in WSN for forest fire detection. Wireless Personal Communications, 109(4), 2561–2605.
Vikram, R., Sinha, D., De, D., & Das, A. K. (2020). EEFFL: energy efficient data forwarding for forest fire detection using localization technique in wireless sensor network. Wireless Networks, 26(7), 5177–5205.
Ghosh, M., Sushil, R., & Ghosh, K. (2019). Detecting and reporting forest fire through deployment of three dimensional multi-sink wireless sensor network. In 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), IEEE, (pp. 1–5).
Jilbab, A., & Bourouhou, A. (2020). Efficient forest fire detection system based on data fusion applied in wireless sensor networks. International Journal on Electrical Engineering and Informatics, 12(1), 1–18.
Arjun, D., & Hanumanthaiah, A. (2020). Wireless Sensor Network Framework for Early Detection and Warning of Forest Fire. In 2020 International Conference on Inventive Computation Technologies (ICICT), IEEE, (pp. 186–191).
Devadevan, V, & Sankaranarayanan, S. (2019). Forest fire information system using wireless sensor network. In Environmental Information Systems: Concepts, Methodologies, Tools, and Applications, IGI Global, (pp. 894–911).
Kadir, E.A., Rosa, S.L., & Yulianti, A. (2018). Application of WSNs for detection land and forest fire in Riau Province Indonesia. In 2018 International Conference on Electrical Engineering and Computer Science (ICECOS), IEEE, (pp. 25–28).
El Khediri, S., Khan, R. U., Nasri, N., & Kachouri, A. (2020). MW-LEACH: Low energy adaptive clustering hierarchy approach for WSN. IET Wireless Sensor Systems, 10(3), 126–129.
Mehra, P. S., Doja, M. N., & Alam, B. (2020). Fuzzy based enhanced cluster head selection (FBECS) for WSN. Journal of King Saud University-Science, 32(1), 390–401.
Shu, T., Chen, J., Bhargava, V. K., & de Silva, C. W. (2019). An energy-efficient dual prediction scheme using LMS filter and LSTM in wireless sensor networks for environment monitoring. IEEE Internet of Things Journal, 6(4), 6736–6747.
Grover, K., Kahali, D., Verma, S., & Subramanian, B. (2020). WSN-based system for forest fire detection and mitigation. In Emerging Technologies for Agriculture and Environment, Springer, Singapore, (pp. 249260).
Ghrab, D., Jemili, I., Belghith, A., Mosbah, M. (2020). Context‐aware routing framework for duty‐cycled wireless sensor networks. In Concurrency and Computation: Practice and Experience, (p. e5958).
El Ghazi, A., Aarab, Z., & Ahiod, B., et.al. (2017). Context-Aware Routing Protocol for Mobile WSN: Fire Forest Detection. In International Conference of Cloud Computing Technologies and Applications, Springer, Cham (pp. 380–391).
Logambigai, R., Kannan, A., et al. (2016). Fuzzy logic based unequal clustering for wireless sensor networks. Wireless Networks, 22(3), 945–957.
Arjunan, S., & Sujatha, P., et. al. (2018). Lifetime maximization of wireless sensor network using fuzzy based unequal clustering and ACO based routing hybrid protocol. Applied Intelligence, pp. 1–18.
Robinson, Y. H., Julie, E. G., & Kumar, R. (2019). Probability-based cluster head selection and fuzzy multipath routing for prolonging lifetime of wireless sensor networks. Peer-to-Peer Networking and Applications, 12(5), 1061–1075.
Janakiraman, S. (2020). An energy-proficient clustering-inspired routing protocol using improved Bkd-tree for enhanced node stability and network lifetime in wireless sensor networks. International Journal of Communication Systems, 33(16), e4575.
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Vinodhini, R., Gomathy, C. Fuzzy Based Unequal Clustering and Context-Aware Routing Based on Glow-Worm Swarm Optimization in Wireless Sensor Networks: Forest Fire Detection. Wireless Pers Commun (2021). https://doi.org/10.1007/s11277-021-08191-y
- Sensor networks
- Optimization algorithm
- Routing protocol
- Context aware
- Fuzzy logic
- Fire detection in forest