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Particle-Water Wave Optimization for Secure Routing in Wireless Sensor Network Using Cluster Head Selection

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Abstract

Wireless sensor network (WSN) has some great advantages, such as flexible communication, low power consumption, and low cost. In view of the WSN clustering algorithm, the dynamic cluster head selection methods are put forward in order to solve the problem of the unreasonable cluster head selection that may lead to the overlapping coverage and unbalanced energy consumption in the cluster communication. Also, security is an important aspect in the WSN. Various security and routing protocols are developed for increasing the efficiency of packet transmission, but discovering the optimal path without degrading transmission reliability poses a challenging task in the sensor network. Hence, an effective and optimal secure routing algorithm named Particle-Water Wave Optimization (P-WWO) is developed in this research for routing the data packets in secure path. The proposed P-WWO algorithm is designed by integrating the Particle Swam Optimization (PSO) with the Water Wave Optimization (WWO). The secure route needed to broadcast the data packets is determined through the selection of Cluster Head using the PSO-based cellular automata with fitness measure. However, the fitness measure is computed by considering the factors, like energy, delay, trust, consistency factor, and maintainability factor. Accordingly, the routing path with the minimal distance and less delay is accepted as the optimal path using the proposed P-WWO based on the fitness value. The route maintenance process enables the proposed optimization to decide whether the packets can be transmitted in the selected route or need to re-route the data. Moreover, the proposed P-WWO obtained better performance using the metrics, such as energy balancing index, coverage, number of alive-nodes, and average energy left with the values of 0.9246 99.9%, 144, and 0.666 J, respectively.

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References

  1. Stephen, R. K., Sekar, A. C., & Dinakaran, K. (2019). Sectional transmission analysis approach for improved reliable transmission and secure routing in wireless sensor networks. Cluster Computing, 22(2), 3759–3770.

    Article  Google Scholar 

  2. Rathee, M., Kumar, S., Gandomi, A. H., Dilip, K., Balusamy, B., & Patan, R. (2019). Ant colony optimization based quality of service aware energy balancing secure routing algorithm for wireless sensor networks. IEEE Transactions on Engineering Management, 68(1), 170–182.

    Article  Google Scholar 

  3. Saini, K., & Ahlawat, P. (2019) A trust-based secure hybrid framework for routing in WSN. In: Recent findings in intelligent computing techniques. Singapore: Springer (pp. 585–591).

  4. Krishnaveni, M. M., Selvakumar, G., & Devi, M. S. A. (2019). Reliable data transmission in wireless network using secure trust based routing.

  5. Kaiwartya, O., Abdullah, A. H., Cao, Y., Altameem, A., Prasad, M., Lin, C. T., & Liu, X. (2016). Internet of vehicles: Motivation, layered architecture, network model, challenges, and future aspects. IEEE Access, 4, 5356–5373.

    Article  Google Scholar 

  6. Cao, Y., Wang, T., Kaiwartya, O., Min, G., Ahmad, N., & Abdullah, A. H. (2016). An EV charging management system concerning drivers’ trip duration and mobility uncertainty. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(4), 596–607.

    Article  Google Scholar 

  7. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.

    Article  Google Scholar 

  8. Kavitha, M., & Geetha, B. G. (2019). An efficient city energy management system with secure routing communication using WSN. Cluster Computing, 22(6), 13131–13142.

    Article  Google Scholar 

  9. Shi, Q., Qin, L., Ding, Y., Xie, B., Zheng, J., & Song, L. (2020). Information-aware secure routing in wireless sensor networks. Sensors, 20(1), 165.

    Article  Google Scholar 

  10. Wang, Y., Attebury, G., & Ramamurthy, B. (2006). A survey of security issues in wireless sensor networks.

  11. Yu, Y., Li, K., Zhou, W., & Li, P. (2012). Trust mechanisms in wireless sensor networks: Attack analysis and countermeasures. Journal of Network and Computer Applications, 35(3), 867–880.

    Article  Google Scholar 

  12. Vasudeva, A., & Sood, M. (2018). Survey on sybil attack defense mechanisms in wireless ad hoc networks. Journal of Network and Computer Applications, 120, 78–118.

    Article  Google Scholar 

  13. Dhanvijay, R., Pande, M., & Wajurakar, S. (2019). Energy optimization in wireless sensor networks using trust-aware routing algorithm.

  14. Tang, D., Jiang, T., & Ren, J. (2010). Secure and energy aware routing (sear) in wireless sensor networks. In IEEE global telecommunications conference GLOBECOM (pp. 1–5).

  15. Abdulrahman, S., & Raisi, J. A. (2020) A review on congestion management methodologies and its applications. Journal of Computational Mechanics, Power System and Control 3(3).

  16. Rodrigues, P., & John, J. (2020). Joint trust: An approach for trust-aware routing in WSN. Wireless Networks, 26(3), 3553–3568.

    Article  Google Scholar 

  17. Perkins, C. E., & Bhagwat, P. (1994). Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. ACM SIGCOMM Computer Communication Review, 24(4), 234–244.

    Article  Google Scholar 

  18. Johnson, D. B., Maltz, D. A., & Broch, J. (2001). DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks. Ad hoc Networking, 5(1), 139–172.

    Google Scholar 

  19. Rewadkar, D., & Doye, D. (2018). Traffic-aware routing protocol in VANET using adaptive autoregressive crow search algorithm. Journal of Networking and Communication Systems, 1(1), 36–42.

    Google Scholar 

  20. Draves, R., Padhye, J., & Zill, B. (2004). Comparison of routing metrics for static multi-hop wireless networks. ACM SIGCOMM Computer Communication Review, 34(4), 133–144.

    Article  Google Scholar 

  21. Zahariadis, T., Leligou, H., Karkazis, P., Trakadas, P., Papaefstathiou, I., Vangelatos, C., & Besson, L. (2010). Design and implementation of a trust-aware routing protocol for large WSNs. International Journal of Network Security & Its Applications (IJNSA), 2(3), 52–68.

    Article  Google Scholar 

  22. Mohan, C. R., & Reddy, A. V. (2018). T-whale: Trust and whale optimization model for secure routing in mobile ad-hoc network. International Journal of Artificial Life Research., 8(2), 67–79.

    Article  Google Scholar 

  23. Srinivas, S., & Santhirani, Ch. (2020). Hybrid particle swarm optimization-deep neural network model for speaker recognition. Multimedia Research, 3(1), 1–10.

    Google Scholar 

  24. Ahmed, A. A., Latiff, L. A., Sarijari, M. A., Fisal, N. (2008). Real-time routing in wireless sensor networks. In Wireless sensor networks.

  25. Sun, Z., Wei, M., Zhang, Z., & Qu, G. (2019). Secure routing protocol based on multi-objective ant-colony-optimization for wireless sensor networks. Applied Soft Computing, 77, 366–375.

    Article  Google Scholar 

  26. 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.

    Article  Google Scholar 

  27. 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.

    Article  Google Scholar 

  28. Mythili, V., Suresh, A., Devasagayam, M. M., & Dhanasekaran, R. (2019). SEAT-DSR: Spatial and energy aware trusted dynamic distance source routing algorithm for secure data communications in wireless sensor networks. Cognitive Systems Research, 58, 143–155.

    Article  Google Scholar 

  29. Beheshtiasl, A., & Ghaffari, A. (2019). Secure and trust-aware routing scheme in wireless sensor networks. Wireless Personal Communications, 107(4), 1799–1814.

    Article  Google Scholar 

  30. Singh, K., & Malhotra, J. (2018). Fuzzy link cost estimation based adaptive tree algorithm for routing optimization in wireless sensor networks using reinforcement learning. Wireless Sensor Networks Using Reinforcement Learning, 8(3), 151–164.

    Google Scholar 

  31. Rodrigues, P., & John, J. (2020). Joint trust: An approach for trust-aware routing in WSN. Wireless Networks, 26, 3553–3568.

    Article  Google Scholar 

  32. Singh, K., & Malhotra, J. (2019). Reinforcement learning-based real time search algorithm for routing optimisation in wireless sensor networks using fuzzy link cost estimation. International Journal of Communication Networks and Distributed Systems, 22(4), 363.

    Article  Google Scholar 

  33. Pattnaik, S., & Sahu, P. K. (2020). Assimilation of fuzzy clustering approach and EHO-Greedy algorithm for efficient routing in WSN. Wireless Sensor Networks, 33(8), 20.

    Google Scholar 

  34. Vinitha, A., Rukmini, M. S. S., & Sunehra, D. (2020). Energy-efficient multihop routing in WSN using the hybrid optimization algorithm. Wireless Sensor Networks, 33(12), 20.

    Google Scholar 

  35. Elhoseny, M., Rajan, R. S., & Hammoudeh, M. (2020). Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks. International Journal of Distributed Sensor Networks, 16, 1550147720949133.

    Article  Google Scholar 

  36. Balachandra, M., Prema, K. V., & Makkithaya, K. (2014). Multiconstrained and multipath QoS aware routing protocol for MANETs. Wireless Networks, 20(8), 2395–2408.

    Article  Google Scholar 

  37. Yadav, A. K., & Tripathi, S. (2017). QMRPRNS: Design of QoS multicast routing protocol using reliable node selection scheme for MANETs. Peer-to-Peer Networking and Applications, 10(4), 897–909.

    Article  Google Scholar 

  38. Zhan, Z. H., Zhang, J., Li, Y., & Chung, H. S. H. (2009). Adaptive particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics Part B (Cybernetics), 39(6), 1362–1381.

    Article  Google Scholar 

  39. Kumar, N., & Kim, J. (2013). ELACCA: Efficient learning automata based cell clustering algorithm for wireless sensor networks. Wireless Personal Communications, 73(4), 1495–1512.

    Article  Google Scholar 

  40. Zheng, Y. J. (2015). Water wave optimization: A new nature-inspired metaheuristic. Computers & Operations Research, 55, 1–11.

    Article  MathSciNet  MATH  Google Scholar 

  41. Chen, Z., He, M., Liang, W., & Chen, K. (2015). Trust-aware and low energy consumption security topology protocol of wireless sensor network. Journal of Sensors, 6, 7.

    Google Scholar 

  42. Wang, B., Chen, X., & Chang, W. (2014). A light-weight trust-based QoS routing algorithm for ad hoc networks. Pervasive and Mobile Computing, 13, 164–180.

    Article  Google Scholar 

  43. Palaniappan, S., & Chellan, K. (2015). Energy-efficient stable routing using QoS monitoring agents in MANET. EURASIP Journal on Wireless Communications and Networking, 1, 1–11.

    Article  Google Scholar 

  44. Wang, Y., Li, D., & Dong, N. (2018). Cellular automata malware propagation model for WSN based on multi-player evolutionary game. IET Networks, 7(3), 129–135.

    Article  Google Scholar 

  45. Byun, H., & Yu, J. (2014). Cellular-automaton-based node scheduling control for wireless sensor networks. IEEE Transactions on Vehicular Technology, 63(8), 3892–3899.

    Article  Google Scholar 

  46. Zhang, F., Wang, X., Li, P., & Zhang, L. (2016). An energy aware cellular learning automata based routing algorithm for opportunistic networks. International Journal of Grid and Distributed Computing, 9(2), 255–272.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Sanjay Ghodawat University, Kolhapur, Maharashtra, 416118, India

    Pradeep Sadashiv Khot

  2. Department of Electronics and Communication Engineering, KLE Dr. M.S. Sheshgiri College of Engineering & Technology, Belagavi, Karnataka, 590008, India

    Udaykumar Naik

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  1. Pradeep Sadashiv Khot
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Correspondence to Pradeep Sadashiv Khot.

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Khot, P.S., Naik, U. Particle-Water Wave Optimization for Secure Routing in Wireless Sensor Network Using Cluster Head Selection. Wireless Pers Commun 119, 2405–2429 (2021). https://doi.org/10.1007/s11277-021-08335-0

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