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Distributed Self Intermittent Fault Diagnosis in Dense Wireless Sensor Network
A distributed sensor network (DSN) is a grouping of low-power and low-cost sensor nodes (SNs) that are stochastically placed in a large-scale area for monitoring regions and enabling various applications. The quality of service in DSN is impacted by the sporadic appearance of defective sensor nodes, especially over the dense wireless network. Due to that, sensor nodes are affected, which reduces network performance during communication. In recent years, the majority of the fault detection techniques in use rely on the neighbor's sensing data over the dense sensor network to determine the fault state of SNs, and based on these, the self-diagnosis is done by receiving information on statistics, thresholds, majority voting, hypothetical testing, comparison, or machine learning. As a result, the false data positive rate (FDPR), detection data accuracy (DDA), and false data alarm rate (FDAR) of these defect detection algorithms are low. Due to high energy expenditure and long detection delay these approaches are not suitable for large scale. In this paper, an enhanced three-sigma edit test-based distributed self-fault dense diagnosis (DSFDD3SET) algorithm is proposed. The performance of the proposed DSFDD3SET has been evaluated using Python, and MATLAB. The experimental results of the DSFDD3SET have been compared with the existing distributed self-fault diagnosis algorithm. The experimental results efficacy outperforms the existing algorithms.
Keywords
Distributed Sensor Network, Fault Diagnosis, Statistical Method, Intermittent Fault, KNN, Three Sigma Edit Test, Self-Intermittent.
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- Ju Y, Tian X, Liu H, Ma L. Fault detection of networked dynamical systems: A survey of trends and techniques. International Journal of Systems Science. 2021 Dec 10; 52(16):3390-409.
- Cao L, Yue Y, Zhang Y. A novel fault diagnosis strategy for heterogeneous wireless sensor networks. Journal of Sensors. 2021 Aug 6; 2021:1-8.
- Sumathi J, Velusamy RL. A review on distributed cluster based routing approaches in mobile wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing. 2021 Jan; 12:835-49.
- Shukla R, Kumar A, Niranjan V. A Survey: Faults, Fault-tolerance & Fault Detection Techniques in WSN. In2022 5th International Conference on Contemporary Computing and Informatics (IC3I) 2022 Dec 14 (pp. 1761-1766). IEEE.
- Narayan V, Daniel AK. RBCHS: Region-based cluster head selection protocol in wireless sensor network. In Proceedings of Integrated Intelligence Enable Networks and Computing: IIENC 2020 2021 (pp. 863-869). Springer Singapore.
- Sarmasti Z, Nobahary S, Nia NH, Abdi GH. FDCD: Fault Detection Method in Clustered WSN Based on Distributed Mode. AdHoc & Sensor Wireless Networks. 2022 Jul 1; 52.
- Loganathan S, Arumugam J, Chinnababu V. An energy‐efficient clustering algorithm with self‐diagnosis data fault detection and prediction for wireless sensor networks. Concurrency and Computation: Practice and Experience. 2021 Sep 10; 33(17):e6288.
- Kumar D, Swain RR, Senapati BR, Khilar PM. Distributed Traversal Based Fault Diagnosis for Wireless Sensor Network. Architectural Wireless Networks Solutions and Security Issues. 2021:121-49.
- Niu Y, Sheng L, Gao M, Zhou D. Distributed intermittent fault detection for linear stochastic systems over sensor network. IEEE Transactions on Cybernetics. 2021 Feb 19; 52(9):9208-18.
- Aydin MA, Karabekir B, Zaim AH. Energy efficient clustering-based mobile routing algorithm on WSNs. IEEE Access. 2021 Jun 21; 9:89593-601.
- Huang DW, Liu W, Bi J. Data tampering attacks diagnosis in dynamic wireless sensor networks. Computer Communications. 2021 Apr 15; 172:84-92.
- Rafeh R. Proposing a distributed fault detection algorithm for wireless sensor networks. Soft Computing Journal. 2021 May 23; 2(2):26-35.
- Sharma S, Kaur A. Survey on wireless sensor network, Its Applications and Issues. In Journal of Physics: Conference Series 2021 Jul 1 (Vol. 1969, No. 1, p. 012042). IOP Publishing.
- Babu N, Santhosh Kumar SV. Comprehensive analysis on sensor node fault management schemes in wireless sensor networks. International Journal of Communication Systems. 2022 Dec; 35(18):e5342.
- Haq MZ, Khan MZ, Rehman HU, Mehmood G, Binmahfoudh A, Krichen M, Alroobaea R. An adaptive topology management scheme to maintain network connectivity in Wireless Sensor Networks. Sensors. 2022 Apr 8; 22(8):2855.
- Panda M, Khilar PM. Distributed self fault diagnosis algorithm for large scale wireless sensor networks using modified three sigma edit test. Ad Hoc Networks. 2015 Feb 1; 25:170-84.
- Panda M, Khilar PM. Distributed Byzantine fault detection technique in wireless sensor networks based on hypothesis testing. Computers & Electrical Engineering. 2015 Nov 1; 48:270-85.
- Bala I, Ahuja K, Arora K, Mandal D. A comprehensive survey on heterogeneous cognitive radio networks. Comprehensive Guide to Heterogeneous Networks. 2023 Jan 1:149-78.
- Hajipour Z, Barati H. EELRP: energy efficient layered routing protocol in wireless sensor networks. Computing. 2021 Dec; 103(12):2789-809.
- Sujihelen L, Boddu R, Murugaveni S, Arnika M, Haldorai A, Reddy PC, Feng S, Qin J. Node replication attack detection in distributed wireless sensor networks. Wireless Communications and Mobile Computing. 2022 May 31; 2022:1-1.
- Ben Gouissem B, Gantassi R, Hasnaoui S. Energy efficient grid based k‐means clustering algorithm for large scale wireless sensor networks.
- International Journal of Communication Systems. 2022 Sep 25; 35(14):e5255.
- Khalifa B, Al Aghbari Z, Khedr AM. A distributed self-healing coverage hole detection and repair scheme for mobile wireless sensor networks. Sustainable Computing: Informatics and Systems. 2021 Jun 1; 30:100428.
- Swain RR, Khilar PM, Bhoi SK. Underlying and persistence fault diagnosis in wireless sensor networks using majority neighbors’ co-ordination approach. Wireless Personal Communications. 2020 Mar; 111:763-98.
- Panda M, Gouda BS, Panigrahi T. Distributed online fault diagnosis in wireless sensor networks. Design Frameworks for Wireless Networks. 2020:197-221.
- Ju Y, Tian X, Liu H, Ma L. Fault detection of networked dynamical systems: A survey of trends and techniques. International Journal of Systems Science. 2021 Dec 10; 52(16):3390-409.
- Ahmadi SH, Khosrowjerdi MJ. Fault detection Automation in Distributed Control Systems using Data-driven methods: SVM and KNN. TechRxiv. 2021 Aug 2:1-8.
- Choudhary A, Kumar S, Sharma KP. RFDCS: A reactive fault detection and classification scheme for clustered wsns. Peer-to-Peer Networking and Applications. 2022 May; 15(3):1705-32.
- Sahu S, Silakari S. Distributed multilevel k-coverage energy-efficient fault-tolerant scheduling for wireless sensor networks. Wireless Personal Communications. 2022 Jun; 124(4):2893-922.
- Yasir Abdullah R, Mary Posonia A, Barakkath Nisha U. An Enhanced Anomaly Forecasting in Distributed Wireless Sensor Network Using Fuzzy Model. International Journal of Fuzzy Systems. 2022 Oct; 24(7):3327-47.
- Sahu S, Silakari S. A Robust Distributed Clustered Fault-Tolerant Scheduling for Wireless Sensor Networks (RDCFT). InInternational Conference on Machine Intelligence and Signal Processing 2022 Mar 12 (pp. 81-93). Singapore: Springer Nature Singapore.
- Saeed U, Jan SU, Lee YD, Koo I. Fault diagnosis based on extremely randomized trees in wireless sensor networks. Reliability engineering & system safety. 2021 Jan 1; 205:107284.
- de Brito JA, Totte DR, Silva FO, Junior JR, Henriques FD, Tarrataca L, Haddad DB, de Assis LS. Memetic algorithm applied to topology control optimization of a wireless sensor network. Wireless Networks. 2022 Nov; 28(8):3677-97.
- Chen X. Fault detection method and simulation based on abnormal data analysis in wireless sensor networks. Journal of Sensors. 2021 Dec 16; 2021:1-1.
- Mittal M, De Prado RP, Kawai Y, Nakajima S, Muñoz-Expósito JE. Machine learning techniques for energy efficiency and anomaly detection in hybrid wireless sensor networks. Energies. 2021 May 27; 14(11):3125.
- Prasad R, Baghel RK. Self-Detection Based Fault Diagnosis for Wireless Sensor Networks. Ad Hoc Networks. 2023 Jul 7:103245.
- Katkar P, Pawar A, Zalte S, Katkar S. Node Failure Management to Improve the Performance of Wireless Sensor Networks. In Recent Trends in Intensive Computing 2021 (pp. 486-491). IOS Press.
- Ibrahim DS, Mahdi AF, Yas QM. Challenges and issues for wireless sensor networks: A survey. J. Glob. Sci. Res. 2021 Jan;6(1):1079-97.
- Gouda BS, Panda M, Panigrahi T, Das S, Appasani B, Acharya O, Zawbaa HM, Kamel S. Distributed Intermittent Fault Diagnosis in Wireless Sensor Network Using Likelihood Ratio Test. IEEE Access. 2023 Jan 13; 11:6958-72.
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