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Hybrid Simulated Annealing with Lion Swarm Optimization Algorithm with Modified Elliptic Curve Cryptography for Secured Data Transmission Over Wireless Sensor Networks (WSN)


Affiliations
1 Department of Computer Science, Periyar University, Salem, Tamil Nadu, India
2 Department of Computer Science, Periyar University Constituent College of Arts and Science, Harur, Dharmapuri, Tamil Nadu, India
 

The security of data processing has become an important factor in the present scenario due to the rapid growth of the internet. Especially, Wireless Sensor Networks (WSNs) face complicated challenges in their vulnerable corrupted sensor nodes. In the earlier work, Enhanced Lion Swarm Optimization Algorithm and Centralized Authentications (ELSOA-CAs) scheme has been proposed for achieving ideal, quicker, and energy efficient data transmissions. But, in the earlier work, a congestion-aware multipath routing mechanism is not considered. Moreover, for the bigger file, the security is not still strong. This security issue is addressed in the proposed work by using Hybrid Simulated Annealing with Lion Swarm Optimization and Centralized Authentication (HSALSO-CA) mechanisms. In the proposed technical work, optimum, quicker, and energy-efficient data transmission is highlighted to guarantee that the decision-making regarding tomato crops is achieved with accuracy. In this research work, multipath routing is presented to ensure that the data transmission is accelerated. In this work, rapid multipath routing is formulated by choosing the best forwarder nodes that meet limitations such as delay and energy. Optimal Forwarder Node Selection employing Hybrid Simulated Annealing with Lion Swarm Optimization Algorithm (HSALSOA) is used. The Simulated Annealing algorithm is hybridized as it emphasizes optimal local and global search capability for the bigger network. Secured data transmission employing Modified Elliptic Curve Cryptographies (MECCs) algorithm guarantees increased security for congestion-sensitive multipath routing mechanisms. It is proven from the simulation outcomes that the proposed ELSOA-CA model yields superior performance in terms of enhanced throughputs, elongated network lives with reduced utilization of energies, and delays in contrast to available techniques.

Keywords

Aggregation, Security, Lion Swarm Optimization, Forwarder Nodes, Centralized Authentication, Secured Data Transmission.
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  • Orhan, O. (2016). Energy neutral and low power wireless communications (Doctoral dissertation, Polytechnic Institute of New York University).
  • Li, J., Liu, W., Wang, T., Song, H., Li, X., Liu, F., & Liu, A. (2019). Battery-friendly relay selection scheme for prolonging the lifetimes of sensor nodes in the Internet of Things. IEEE Access, 7, 33180-33201.
  • Wang, C., He, Y., Yu, F. R., Chen, Q., & Tang, L. (2017). Integration of networking, caching, and computing in wireless systems: A survey, some research issues, and challenges. IEEE Communications Surveys & Tutorials, 20(1), 7-38.
  • Shaf, A., Ali, T., Draz, U., & Yasin, S. (2018). Energy Based Performance analysis of AODV Routing Protocol under TCP and UDP Environments. EAI Endorsed Transactions on Energy Web, 5(17).
  • Yang, L., Zhu, H., Kang, K., Luo, X., Qian, H., & Yang, Y. (2018, April). Distributed censoring with energy constraint in wireless sensor networks. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6428-6432). IEEE.
  • Randhawa, S., & Jain, S. (2017). Data aggregation in wireless sensor networks: Previous research, current status and future directions. Wireless Personal Communications, 97(3), 3355-3425.
  • Tomić, I., & McCann, J. A. (2017). A survey of potential security issues in existing wireless sensor network protocols. IEEE Internet of Things Journal, 4(6), 1910-1923.
  • Kharb, K., Sharma, B., & Trilok, C. A. (2016). Reliable and congestion control protocols for wireless sensor networks. International Journal of Engineering and Technology Innovation, 6(1), 68.
  • Anand, N., Varma, S., Sharma, G., &Vidalis, S. (2018). Enhanced reliable reactive routing (ER3) protocol for multimedia applications in 3D wireless sensor networks. Multimedia Tools and Applications, 77(13), 16927-16946.
  • Kumaravel, K., &Anusuya, N. (2018). A SURVEY ON CONGESTION CONTROL SYSTEM IN WIRELESS SENSOR NETWORKS. International Journal for Research in Science Engineering & Technology, 5(9), 7-11.
  • Harish, V. S. K. V., & Kumar, A. (2016). A review on modeling and simulation of building energy systems. Renewable and sustainable energy reviews, 56, 1272-1292.
  • Rosset, V., Paulo, M. A., Cespedes, J. G., & Nascimento, M. C. (2017). Enhancing the reliability on data delivery and energy efficiency by combining swarm intelligence and community detection in large-scale WSNs. Expert Systems with Applications, 78, 89-102.
  • Bhatia, A., &Hansdah, R. C. (2016). TRM-MAC: A TDMA-based reliable multicast MAC protocol for WSNs with flexibility to trade-off between latency and reliability. Computer Networks, 104, 79-93.
  • Mohanty, P., & Kabat, M. R. (2016). Energy efficient structure-free data aggregation and delivery in WSN. Egyptian Informatics Journal, 17(3), 273-284.
  • Faheem, M., Butt, R. A., Raza, B., Ashraf, M. W., Ngadi, M. A., &Gungor, V. C. (2019). Energy efficient and reliable data gathering using internet of software-defined mobile sinks for WSNs-based smart grid applications. Computer Standards & Interfaces, 66, 103341.
  • Elappila, M., Chinara, S., &Parhi, D. R. (2018). Survivable path routing in WSN for IoT applications. Pervasive and Mobile Computing, 43, 49-63.
  • Sharma, B., Srivastava, G., & Lin, J. C. W. (2020). A bidirectional congestion control transport protocol for the internet of drones. Computer Communications, 153, 102-116.
  • Vinitha, A., & Rukmini, M. S. S. (2019). Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm. Journal of King Saud University-Computer and Information Sciences.
  • Devi, V. S., Ravi, T., & Priya, S. B. (2020). Cluster Based Data Aggregation Scheme for Latency and Packet Loss Reduction in WSN. Computer Communications, 149, 36-43.
  • Rekha, & Gupta, Rajeev. (2021). Elliptic Curve Cryptography based Secure Image Transmission in Clustered Wireless Sensor Networks. International Journal of Computer Networks and Applications. 8. 67. 10.22247/ijcna/2021/207983.
  • Qazi, R., Qureshi, K. N., Bashir, F., Islam, N. U., Iqbal, S., & Arshad, A. (2021). Security protocol using elliptic curve cryptography algorithm for wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 12(1), 547-566.
  • Uma Maheswari P, Ganeshbabu TR, P.Subramaninan, Elliptic Curve Cryptography based Secure Data Communication and Enhance sensor Reliability in Wireless Sensor Network, International Journal of Recent Technology and Engineering (IJRTE), 8(5), 2020.
  • Rajeev Arya and S.C. Sharma, “Energy Optimization of Energy Aware Routing Protocol and Bandwidth Assessment for Wireless Sensor Network”, International Journal of System Assurance Engineering and Management, 9(3), pp. 612-619, 2018.
  • Haseeb, K., Islam, N., Saba, T., Rehman, A., & Mehmood, Z. (2020). LSDAR: A light-weight structure based data aggregation routing protocol with secure internet of things integrated next-generation sensor networks. Sustainable Cities and Society, 54, 101995.
  • Silambarasan, S., & Devi, M. S. (2021). Enhanced Lion Swarm Optimization Algorithm With Centralized Authentication Approach for Secured Data Transmission Over WSN. ICTACT Journal on Communication Technology, 12(3), 2471-2479.
  • W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660–670, 2002.
  • D. Kumar, T. C. Aseri, and R. B. Patel, “EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks,” Computer Communications, vol. 32, no. 4, pp. 662–667, 2009.
  • Lee, H.; Wicke, M.; Kusy, B.; Gnawali, O.; Guibas, L. Data Stashing: Energy-Efficient Information Delivery to Mobile Sinks through Trajectory Prediction. Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, Stockholm, Sweden, 12–16 April 2010; pp. 291–302.
  • Tian, K.; Zhang, B.; Huang, K.; Ma, J. Data Gathering Protocols for Wireless Sensor Networks with Mobile Sinks. Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM 2010), Miami, FA, USA,, 6–10 December 2010; pp. 1–6.
  • Kusy, B.; Lee, H.; Wicke, M.; Milosavljevic, N.; Guibas, L. Predictive QoS Routing to Mobile Sinks in wireless sensor networks. Proceedings of the IEEE International Conference on Information Processing in Sensor Networks (IPSN, 2009), San Francisco, CA, USA, 13–16 April 2009; pp. 109–120.
  • Wang, M.; Heidari, A.A.; Chen, M.; Chen, H.; Zhao, X.; Cai, X. Exploratory differential ant lion-based optimization. Expert Syst. Appl. 2020, 159, 113548.
  • Pierezan, J.; Coelho, L.d.S.; Mariani, V.C.; Goudos, S.K.; Boursianis, A.D.; Kantartzis, N.V.; Antonopoulos, C.S.; Nikolaidis, S. Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization. Technologies 2021,
  • E. Aarts, J. Korst, and W. Michiels, “Simulated annealing,” in Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, K Burke and G. Kendall, Eds., pp. 91–120, Springer US, Boston, Mass, USA, 2nd edition, 2014.
  • Nishanth, R. B., Ramakrishnan, B., & Selvi, M. (2015). Improved signcryption algorithm for information security in networks. International Journal of Computer Networks and Applications (IJCNA), 2(3), 151-157.

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  • Hybrid Simulated Annealing with Lion Swarm Optimization Algorithm with Modified Elliptic Curve Cryptography for Secured Data Transmission Over Wireless Sensor Networks (WSN)

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Authors

S. Silambarasan
Department of Computer Science, Periyar University, Salem, Tamil Nadu, India
M. Savitha Devi
Department of Computer Science, Periyar University Constituent College of Arts and Science, Harur, Dharmapuri, Tamil Nadu, India

Abstract


The security of data processing has become an important factor in the present scenario due to the rapid growth of the internet. Especially, Wireless Sensor Networks (WSNs) face complicated challenges in their vulnerable corrupted sensor nodes. In the earlier work, Enhanced Lion Swarm Optimization Algorithm and Centralized Authentications (ELSOA-CAs) scheme has been proposed for achieving ideal, quicker, and energy efficient data transmissions. But, in the earlier work, a congestion-aware multipath routing mechanism is not considered. Moreover, for the bigger file, the security is not still strong. This security issue is addressed in the proposed work by using Hybrid Simulated Annealing with Lion Swarm Optimization and Centralized Authentication (HSALSO-CA) mechanisms. In the proposed technical work, optimum, quicker, and energy-efficient data transmission is highlighted to guarantee that the decision-making regarding tomato crops is achieved with accuracy. In this research work, multipath routing is presented to ensure that the data transmission is accelerated. In this work, rapid multipath routing is formulated by choosing the best forwarder nodes that meet limitations such as delay and energy. Optimal Forwarder Node Selection employing Hybrid Simulated Annealing with Lion Swarm Optimization Algorithm (HSALSOA) is used. The Simulated Annealing algorithm is hybridized as it emphasizes optimal local and global search capability for the bigger network. Secured data transmission employing Modified Elliptic Curve Cryptographies (MECCs) algorithm guarantees increased security for congestion-sensitive multipath routing mechanisms. It is proven from the simulation outcomes that the proposed ELSOA-CA model yields superior performance in terms of enhanced throughputs, elongated network lives with reduced utilization of energies, and delays in contrast to available techniques.

Keywords


Aggregation, Security, Lion Swarm Optimization, Forwarder Nodes, Centralized Authentication, Secured Data Transmission.

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DOI: https://doi.org/10.22247/ijcna%2F2022%2F212557