Combined Osprey-Chimp Optimization for Cluster Based Routing in Wireless Sensor Networks: Improved DeepMaxout for Node Energy Prediction

Authors

  • Kotagi Basavarajappa Vikhyath Research Scholar, Department of Computer Science and Engineering, East West Institute of Technology, Bengaluru, India | Visvesvaraya Technological University, Belagavi – 590018, India
  • Narasimhaiah Achyutha Prasad Research Supervisor, Department of Computer Science and Engineering, East West Institute of Technology, Bengaluru, India | Visvesvaraya Technological University, Belagavi – 590018, India
Volume: 13 | Issue: 6 | Pages: 12314-12319 | December 2023 | https://doi.org/10.48084/etasr.6542

Received: 19 October 2023 | Revised: 31 October 2023 | Accepted: 2 November 2023 | Online: 22 November 2023


Corresponding author: Kotagi Basavarajappa Vikhyath

Abstract

The significant advances in Wireless Sensor Networks (WSNs) facilitate many latest applications, such as intelligent battlefield, home automation, traffic control, and more. WSNs comprise small autonomously organized sensor nodes that are powered by batteries. The processes of collecting information and data storage, processing, and transmission deplete the energy of these small devices. Energy efficiency is still a major issue to address in WSN routing. Clustering is the best method that has been developed to reduce node energy consumption. However, current clustering methods are unable to effectively distribute the energy requirements of the nodes without considering energy characteristics, number of nodes, and flexibility. This study proposed a new cluster-based routing model for WSNs and emphasized the need for an improved clustering process with new optimization techniques. In particular, the improved DeepMaxout model was adopted to predict the energy of the nodes. Cluster Head (CH) selection is performed considering the nodes' energy as a prime factor. After choosing the CH, the CIOO algorithm incorporates new link quality and trust evaluations while determining the routing process. Finally, a comparison of energy utilization factors was performed between the suggested and traditional approaches.

Keywords:

improved DeepMaxout, osprey-chimp, routing, node energy prediction

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References

I. S. Akila and R. Venkatesan, "A Fuzzy Based Energy-aware Clustering Architecture for Cooperative Communication in WSN," The Computer Journal, vol. 59, no. 10, pp. 1551–1562, Jul. 2016.

A. Rajab, "Genetic Algorithm-Based Multi-Hop Routing to Improve the Lifetime of Wireless Sensor Networks," Engineering, Technology & Applied Science Research, vol. 11, no. 6, pp. 7770–7775, Dec. 2021.

V. K B and D. Brahmanand S. H, "Wireless sensor networks security issues and challenges: A survey," International Journal of Engineering & Technology, vol. 7, no. 3.3, Jun. 2018, Art. no. 89.

M. A. Mahdi, T. C. Wan, A. Mahdi, M. a. G. Hazber, and B. A. Mohammed, "A Multipath Cluster-Based Routing Protocol For Mobile Ad Hoc Networks," Engineering, Technology & Applied Science Research, vol. 11, no. 5, pp. 7635–7640, Oct. 2021.

N. A. Prasad et al., "Delay optimization and energy balancing algorithm for improving network lifetime in fixed wireless sensor networks," Physical Communication, vol. 58, Jun. 2023, Art. no. 102038.

A. Kout, B. Bouaita, A. Beghriche, S. Labed, S. Chikhi, and E.-B. Bourennane, "A Hybrid Optimization Solution for UAV Network Routing," Engineering, Technology & Applied Science Research, vol. 13, no. 2, pp. 10270–10278, Apr. 2023.

S. Ali and R. Kumar, "Hybrid energy efficient network using firefly algorithm, PR-PEGASIS and ADC-ANN in WSN," Sensors International, vol. 3, Jan. 2022, Art. no. 100154.

O. Deepa and J. Suguna, "An optimized QoS-based clustering with multipath routing protocol for Wireless Sensor Networks," Journal of King Saud University - Computer and Information Sciences, vol. 32, no. 7, pp. 763–774, Sep. 2020.

N. A. Prasad and C. D. Guruprakash, "A Two Hop Relay Battery Aware Mote Scheme for Energy Redeemable and Network Lifespan Improvement in WSN," International Journal of Engineering and Advanced Technology, vol. 9, no. 1, pp. 4785–4791, Oct. 2019.

B. Rambabu, A. Venugopal Reddy, and S. Janakiraman, "Hybrid Artificial Bee Colony and Monarchy Butterfly Optimization Algorithm (HABC-MBOA)-based cluster head selection for WSNs," Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 5, pp. 1895–1905, May 2022.

I. K. Shah, T. Maity, Y. S. Dohare, D. Tyagi, D. Rathore, and D. S. Yadav, "ICIC: A Dual Mode Intra-Cluster and Inter-Cluster Energy Minimization Approach for Multihop WSN," IEEE Access, vol. 10, pp. 70581–70594, 2022.

D. Jia, H. Zhu, S. Zou, and P. Hu, "Dynamic Cluster Head Selection Method for Wireless Sensor Network," IEEE Sensors Journal, vol. 16, no. 8, pp. 2746–2754, Apr. 2016.

P. K. Batra and K. Kant, "LEACH-MAC: a new cluster head selection algorithm for Wireless Sensor Networks," Wireless Networks, vol. 22, no. 1, pp. 49–60, Jan. 2016.

D. P. Singh, R. H. Goudar, B. Pant, and S. Rao, "Cluster head selection by randomness with data recovery in WSN," CSI Transactions on ICT, vol. 2, no. 2, pp. 97–107, Jun. 2014.

N. Sirdeshpande and V. Udupi, "Fractional lion optimization for cluster head-based routing protocol in wireless sensor network," Journal of the Franklin Institute, vol. 354, no. 11, pp. 4457–4480, Jul. 2017.

S. H. Kang and T. Nguyen, "Distance Based Thresholds for Cluster Head Selection in Wireless Sensor Networks," IEEE Communications Letters, vol. 16, no. 9, pp. 1396–1399, Sep. 2012.

B. Saoud, I. Shayea, M. H. Azmi, and A. A. El-Saleh, "New scheme of WSN routing to ensure data communication between sensor nodes based on energy warning," Alexandria Engineering Journal, vol. 80, pp. 397–407, Oct. 2023.

Y. Zhang, L. Liu, M. Wang, J. Wu, and H. Huang, "An improved routing protocol for raw data collection in multihop wireless sensor networks," Computer Communications, vol. 188, pp. 66–80, Apr. 2022.

G. Thahniyath and M. Jayaprasad, "Secure and load balanced routing model for wireless sensor networks," Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 7, pp. 4209–4218, Jul. 2022.

F. S. Alrayes et al., "Dwarf Mongoose Optimization-Based Secure Clustering with Routing Technique in Internet of Drones," Drones, vol. 6, no. 9, Sep. 2022, Art. no. 247.

C. Kaur, S. M. Hassen, M. S. A. Boush, and H. Anandaram, "Energy Prediction for Mobile Sink Placement by Deep Maxout Network in WSN," Journal of Advances in Information Technology, vol. 14, no. 1, pp. 112–121, 2023.

P. Ramachandran, B. Zoph, and Q. V. Le, "Swish: a self-gated activation function," arXiv preprint arXiv:1710.05941, vol. 7, no. 1, 2017.

C. Nwankpa, W. Ijomah, A. Gachagan, and S. Marshall, "Activation Functions: Comparison of trends in Practice and Research for Deep Learning." arXiv, Nov. 08, 2018.

N. Rouissi, H. Gharsellaoui, and S. Bouamama, "Improvement of Watermarking-LEACH Algorithm Based on Trust for Wireless Sensor Networks," Procedia Computer Science, vol. 159, pp. 803–813, Jan. 2019.

"Effect on Packet Delivery Ratio (PDR) & Throughput in Wireless Sensor Networks Due to Black Hole Attack," International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 12S, pp. 428–432, Dec. 2019.

R. Mahima, K. S. Kiruthik Ruba, and A. Pushpalatha, "Energy Optimized Data Routing Using PSO in WSN," International Journal of Emerging Technology and Innovative Engineering, vol. 6, no. 3, pp. 106–115, Mar. 2020.

Y. Meraihi, A. B. Gabis, S. Mirjalili, and A. Ramdane-Cherif, "Grasshopper Optimization Algorithm: Theory, Variants, and Applications," IEEE Access, vol. 9, pp. 50001–50024, 2021.

H. Sharma, G. Hazrati, and J. C. Bansal, "Spider Monkey Optimization Algorithm," in Evolutionary and Swarm Intelligence Algorithms, J. C. Bansal, P. K. Singh, and N. R. Pal, Eds. Cham, Switzerland: Springer International Publishing, 2019, pp. 43–59.

S. Arora and S. Singh, "Butterfly optimization algorithm: a novel approach for global optimization," Soft Computing, vol. 23, no. 3, pp. 715–734, Feb. 2019.

M. Khishe and M. R. Mosavi, "Chimp optimization algorithm," Expert Systems with Applications, vol. 149, Jul. 2020, Art. no. 113338.

M. Dehghani and P. Trojovský, "Osprey optimization algorithm: A new bio-inspired metaheuristic algorithm for solving engineering optimization problems," Frontiers in Mechanical Engineering, vol. 8, 2023.

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How to Cite

[1]
K. B. Vikhyath and N. A. Prasad, “Combined Osprey-Chimp Optimization for Cluster Based Routing in Wireless Sensor Networks: Improved DeepMaxout for Node Energy Prediction”, Eng. Technol. Appl. Sci. Res., vol. 13, no. 6, pp. 12314–12319, Dec. 2023.

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