Open Access Subscription Access
Trust-Based Co-Operative Cross-Layer Routing Protocol for Industrial Wireless Sensor Networks
One of the significant applications of wireless sensor networks is Industrial Wireless Sensor Network (IWSN). These IWSNs are set up in manufacturing premises for security, manufacturing administration, data collection, and control, etc. The measured data is transmitted from the nodes to the administrative controller and data analysis systems in such networks. Real-time communication and data reliability are the two major concerns that need trusted relay nodes for further data transfer. Most of the trust-based routing protocol models in IWSN are based on detecting misbehavior at the network layer only. These approaches result in higher values of false-positive rate since the normal failure of nodes is considered as low trusted nodes. Trust-based Co-operative Cross-layer Routing Protocol (TCCRP) for IWSN is proposed in this paper to reduce the false-positive rate and for QoS parameters improvement. It consists of three phases: trust collection, trust verification, and trust evaluation. Simulation results of the proposed TCCRP protocol show the performance improvement in QoS parameters in terms of throughput, packet delivery ratio, and residual energy with a lesser false positive rate compared to the trust management-based secure routing scheme in an industrial wireless sensor network with fog computing (TMSRS).
WSN, Cross-Layer Design, Trust-Based Routing, QoS, False-Positive Reduction, Cooperative Routing.
- M. Majid, “Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review,” Sensors, vol. 22, no. 6, p. 2087, Jan. 2022, doi: 10.3390/s22062087.
- M. Perisa, T. M. Kuljanic, I. Cvitic, and P. Kolarovszki, “Conceptual model for informing user with innovative smart wearable device in industry 4.0,” Wireless Networks, vol. 27, no. 3, pp. 1615–1626, Apr. 2021, doi: 10.1007/s11276-019-02057-9.
- P. M. Kumar, G. C. Babu, A. Selvaraj, M. Raza, A. K. Luhach, and V. G. Díaz, “Multi-criteria-based approach for job scheduling in industry 4.0 in smart cities using fuzzy logic,” Soft Computing, vol. 25, no. 18, pp. 12059–12074, Sep. 2021, doi: 10.1007/s00500-021-05765-7.
- W. Fang, W. Zhang, W. Chen, Y. Liu, and C. Tang, “TMSRS: Trust management-based secure routing scheme in industrial wireless sensor network with fog computing,” Wireless Networks, vol. 26, no. 5, pp. 3169–3182, 2019.
- S. Yu and J. He, “Providing trusted data for industrial wireless sensor networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2018, no. 1, p. 289, Dec. 2018, doi: 10.1186/s13638-018-1307-y.
- M. Bal, “An industrial Wireless Sensor Networks framework for production monitoring,” 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), pp. 1442-1447. IEEE, 2014, doi: 10.1109/ISIE.2014.6864826.
- L. Liu, G. Han, Y. He, and J. Jiang, “Fault-tolerant event region detection on trajectory pattern extraction for industrial wireless sensor networks,” IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 2072–2080, 2019.
- L. B. Hormann, C. Kastl, H.-P. Bernhard, P. Priller, and A. Springer, “Lifetime security concept for industrial wireless sensor networks,” in 2020 16th IEEE International Conference on Factory Communication Systems (WFCS), pp. 1–8, 2020.
- L. Li, “A secure random key distribution scheme against node replication attacks in industrial wireless sensor systems,” IEEE Transactions on Industrial Informatics, vol. 16, no. 3, pp. 2091–2101, 2019.
- A. Tiab and L. Bouallouche-Medjkoune, “Routing in Industrial Wireless Sensor Networks: A Survey.” Chinese Journal of Engineering, p.7, Feb. 2014. doi: 10.1155/2014/579874.
- J. Duan, D. Yang, H. Zhu, S. Zhang, and J. Zhao, “TSRF: A Trust-Aware Secure Routing Framework in Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 2014, pp. 1– 14, Jan. 2014, doi: 10.1155/2014/209436.
- Z. Teng, C. Du, M. Li, H. Zhang, and W. Zhu, “A Wormhole Attack Detection Algorithm Integrated With the Node Trust Optimization Model in WSNs,” IEEE Sensors Journal, vol. 22, no. 7, pp. 7361–7370, Apr. 2022, doi: 10.1109/JSEN.2022.3152841.
- B. Mbarek, M. Ge, and T. Pitner, “An adaptive anti-jamming system in HyperLedger-based wireless sensor networks,” Wireless Networks, vol. 28, no. 2, pp. 691–703, Feb. 2022, doi: 10.1007/s11276-022-02886-1.
- Y. Lai, “Identifying malicious nodes in wireless sensor networks based on correlation detection,” Computers & Security, vol. 113, p. 102540, Feb. 2022, doi: 10.1016/j.cose.2021.102540.
- Y. Han, H. Hu, and Y. Guo, “Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm,” IEEE Access, vol. 10, pp. 11538–11550, 2022, doi: 10.1109/ACCESS.2022.3144015.
- T. Khan, “ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs,” Future Generation Computer Systems, vol. 125, pp. 921–943, Dec. 2021, doi: 10.1016/j.future.2021.06.049.
- M. Mathapati, T. S. Kumaran, A. Muruganandham, and M. Mathivanan, “Secure routing scheme with multi-dimensional trust evaluation for wireless sensor network,” Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 6, pp. 6047–6055, Jun. 2021, doi: 10.1007/s12652-020-02169-7.
- I. Ahmad, “Analysis of Security Attacks and Taxonomy in Underwater Wireless Sensor Networks,” Wireless Communications and Mobile Computing, vol. 2021, p. e1444024, Dec. 2021, doi: 10.1155/2021/1444024.
- W. Fang, N. Cui, W. Chen, W. Zhang, and Y. Chen, “A trust-based security system for data collecting in smart city,” IEEE Transactions on Industrial Informatics, 2020.
- M. S. Sumalatha and V. Nandalal, “An intelligent cross layer security based fuzzy trust calculation mechanism (CLS-FTCM) for securing wireless sensor network (WSN),” Journal of Ambient Intelligence and Humanized Computing, pp. 1–15, 2020.
- C. Liu and X. Li, “Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks,” Sensors, vol. 20, no. 6, p. 1592, Jan. 2020, doi: 10.3390/s20061592.
- M. Raza, S. Hussain, H. Le-Minh, and N. Aslam, “Novel MAC layer proposal for URLLC in industrial wireless sensor networks,” ZTE Communications, vol. 15, no. S1, pp. 50–59, 2020.
- K. P. Uvarajan and C. Gowri Shankar, “An Integrated Trust Assisted Energy Efficient Greedy Data Aggregation for Wireless Sensor Networks,” Wireless Personal Communications, pp. 1–21, 2020.
- Y. Ren, Z. Zeng, T. Wang, S. Zhang, and G. Zhi, “A trust-based minimum cost and quality aware data collection scheme in P2P network,” Peer-to-Peer Networking and Applications, pp. 1–24, 2020.
- M. Elsharief, M. A. A. El-Gawad, H. Ko, and S. Pack, “EERS: Energy-Efficient Reference Node Selection Algorithm for Synchronization in Industrial Wireless Sensor Networks,” Sensors, vol. 20, no. 15, p. 4095, 2020.
- U. Ghugar, J. Pradhan, S. K. Bhoi, and R. R. Sahoo, “LB-IDS: Securing wireless sensor network using protocol layer trust-based intrusion detection system,” Journal of Computer Networks and Communications, vol. 2019, 2019.
- W. Fang, W. Zhang, W. Chen, Y. Liu, and C. Tang, “TME 2 R: Trust Management-Based Energy Efficient Routing Scheme in Fog-Assisted Industrial Wireless Sensor Network,” in International Conference on 5G for Future Wireless Networks, 2019, pp. 155–173.
- T. Yang, X. Xiangyang, L. Peng, L. Tonghui, and P. Leina, “A secure routing of wireless sensor networks based on trust evaluation model,” Procedia Computer Science, vol. 131, pp. 1156–1163, 2018, doi: 10.1016/j.procs.2018.04.289
- Chinnaswamy S, K A. Trust aggregation authentication protocol using machine learning for IoT wireless sensor networks. Computers and Electrical Engineering 91: pp. 107-130, 2021.
Abstract Views: 36
PDF Views: 1