Wireless Sensor Network Predictions of Dynamic Target Tracking Algorithm for Error Tolerance

Authors

  • Mustafa Hussein Mohammed Al-Mustaqbal University, Hillah, Iraq

DOI:

https://doi.org/10.29304/jqcsm.2024.16.21538

Keywords:

wireless sensor network; mobile network; fault tolerance; target tracking; genetic algorithm

Abstract

The use of wireless sensor networks (WSNs) in tracking moving objects has increased significantly in recent years. Target node coverage, a criterion for choosing the right node or nodes for monitoring moving targets, is described in this research utilizing the proposed algorithm that is based on the combined genetic algorithm and MTR (Multiple Target Research). The suggested approach combines factors according to a basic strategy, and while choosing the right node, better attributes are taken into account. The suggested approach determines which node or nodes are suitable for covering and tracking network objectives based on their degree of overlap, distance to the well, and best remaining energy. Criterion for selecting the appropriate node or nodes for tracking moving targets are presented in the form of target node coverage. In the proposed method, parameters are combined based on a fundamental strategy, and superior characteristics are regarded when selecting the appropriate node. Fewer nodes are positioned in the appropriate coverage region, according to the results. Furthermore, given that the communication

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References

Najavi, Mohammad Javad, 2013, investigation of reliable routing methods in wireless sensor networks, BA project, Azad University

Qolipour Moghadam, Milad, Saleh Namdi, Mohammad, 2015, a review of clustering methods in wireless sensor networks, the first national conference of electrical engineering, Islamic Azad University, Langrod branch.

Alizadeh, Elham and Sanjabi, Saeed and Malekshahi, Amir, 2013, fault tolerance in cloud computing, National Conference of Computer Science and Engineering focusing on national security and sustainable development, Mashhad

Nabai, Golnoosh Sadat and Mousavi, Syed Morteza, 2014, Presenting a new method for topology control in wireless sensor networks in order to increase fault tolerance, International Conference on Applied Research in Information Technology, Computers and Telecommunications, Torbet Heydarieh.

Sheikhi, Hammet and Barkhoda, Seyyed Wafa, 2018, improving fault tolerance in wireless sensor networks by creating k-connected networks, the first international conference on smart city challenges and strategies, Shiraz

Qu, Z., Xu, H., Zhao, X., Tang, H., Wang, J., & Li, B. (2022). A fault-tolerant sensor scheduling approach for target tracking in wireless sensor networks. Alexandria Engineering Journal, 61(12), 13001-13010.

Hameed, S., Khan, F. I., & Hameed, B. (2019). Understanding security requirements and challenges in Internet of Things (IoT): A review. Journal of Computer Networks and Communications, 2019.

Bhatti, S., Xu, J., & Memon, M. (2011). Clustering and fault tolerance for target tracking using wireless sensor networks. IET wireless sensor systems, 1(2), 66-73.

Paradis, L., & Han, Q. (2017). A survey of fault management in wireless sensor networks. Journal of Network and systems management, 15(2), 171-190.

Yuan, Y., Yi, W., & Choi, W. (2022). Dynamic Sensor Scheduling for Target Tracking in Wireless Sensor Networks with Cost Minimization Objective. IEEE Internet of Things Journal.

JAYA, N. V. (2022). Efficient Cluster Head Selection and Fault Tolerant Routing Method for Mobile Wireless Sensor Networks. Adhoc & Sensor Wireless Networks, 51.

Mahmood, T., Li, J., Pei, Y., Akhtar, F., Butt, S. A., Ditta, A., & Qureshi, S. (2022). An intelligent fault detection approach based on reinforcement learning system in wireless sensor network. The Journal of Supercomputing, 78(3), 3646-3675.

Choudhary, A., Kumar, S., Gupta, S., Gong, M., & Mahanti, A. (2021). FEHCA: A fault-tolerant energy-efficient hierarchical clustering algorithm for wireless sensor networks. Energies, 14(13), 3935.

Adhami, M. H., & Ghazizadeh, R. (2021). Secure multiple target tracking based on clustering intersection points of measurement circles in wireless sensor networks. Wireless Networks, 27(2), 1233-1249.

Qu, Z., & Li, B. (2022). An Energy-Efficient Clustering Method for Target Tracking Based on Tracking Anchors in Wireless Sensor Networks. Sensors, 22(15), 5675.

Zieliski, Z., Chudzikiewicz, J., & Furtak, J. (2019). An approach to integrating security and fault tolerance mechanisms into the military IoT. In Security and Fault Tolerance in Internet of Things (pp. 111-128). Springer, Cham.

Mohamed, N., Al-Jaroodi, J., & Jawhar, I. (2019, January). Towards fault tolerant fog computing for IoT-based smart city applications. In 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0752-0757). IEEE.

Gope, P., Gheraibia, Y., Kabir, S., & Sikdar, B. (2020). A secure IoT-based modern healthcare system with fault-tolerant decision making process. IEEE Journal of Biomedical and Health Informatics.

Zavalyshyn, I., Given-Wilson, T., Legay, A., & Sadre, R. (2020, November). Brief Announcement: Effectiveness of Code Hardening for Fault-Tolerant IoT Software. In International Symposium on Stabilizing, Safety, and Security of Distributed Systems (pp. 317-322). Springer, Cham.

Alfandi, O., Otoum, S., & Jararweh, Y. (2020, April). Blockchain solution for iot-based critical infrastructures: Byzantine fault tolerance. In NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium (pp. 1-4). IEEE.

Samanta, A., Esposito, F., & Nguyen, T. G. (2021). Fault-Tolerant Mechanism for Edge-Based IoT Networks with Demand Uncertainty. IEEE Internet of Things Journal.

Kiadehi, K. B., Rahmani, A. M., & Molahosseini, A. S. (2021). A fault-tolerant architecture for internet-of-things based on software-defined networks. Telecommunication Systems, 77(1), 155-169.

Zhu, B., Joseph, A., & Sastry, S. (2011, October). A taxonomy of cyber attacks on SCADA systems. In 2011 International conference on internet of things and 4th international conference on cyber, physical and social computing (pp. 380-388). IEEE.

Li, Y. X. (2019). Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems. Automatica, 106, 117-123.

Giannarakis, N., Beckett, R., Mahajan, R., & Walker, D. (2019, July). Efficient verification of network fault tolerance via counterexample-guided refinement. In International Conference on Computer Aided Verification (pp. 305-323). Springer, Cham.

Sharma, K., & Yadav, R. N. (2020). An adaptive, fault tolerant, flow-level routing scheme for data center networks. Computer Networks, 175, 107235.

Borja, L. J. (2020). Assessing Priorities towards Achieving Dependable and Secure Computing in the US ICBM Force. Science & Global Security, 28(1), 2-27.

Singh, G., Raj, B., & Sarin, R. K. (2018). Fault-tolerant design and analysis of QCA-based circuits. IET Circuits, Devices & Systems, 12(5), 638-644.

Dreany, H. H., & Roncace, R. (2019). A cognitive architecture safety design for safety critical systems. Reliability Engineering & System Safety, 191, 106555.

Kim, B. S., Kang, S., Lim, J., Kim, K. H., & Kim, K. I. (2017, January). A mobility-based temperature-aware routing protocol for wireless body sensor networks. In 2017 International Conference on Information Networking (ICOIN)(pp. 63-66). IEEE.

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Published

2024-06-30

How to Cite

Hussein Mohammed, M. (2024). Wireless Sensor Network Predictions of Dynamic Target Tracking Algorithm for Error Tolerance . Journal of Al-Qadisiyah for Computer Science and Mathematics, 16(2), Comp. 13–22. https://doi.org/10.29304/jqcsm.2024.16.21538

Issue

Section

Computer Articles