Fuzzy rule-based faulty node classification and management scheme for large scale wireless sensor networks

Fuzzy logic based hardware status analysis of the deployed sensor nodes.Faulty sensor nodes are reused to improve WSNs quality of services (QoS).Data routing algorithm improves reusability of the faulty nodes.Simulations verify the effectiveness of the approach with comparisons. In a wireless sensor network (WSNs), probability of node failure rises with increase in number of sensor nodes within the network. The, quality of service (QoS) of WSNs is highly affected by the faulty sensor nodes. If faulty sensor nodes can be detected and reused for network operation, QoS of WSNs can be improved and will be sustainable throughout the monitoring period. The faulty nodes in the deployed WSN are crucial to detect due to its improvisational nature and invisibility of internal running status. Furthermore, most of the traditional fault detection methods in WSNs do not consider the uncertainties that are inherited in the WSN environment during the fault diagnosis period. Resulting traditional fault detection methods suffer from low detection accuracy and poor performance. To address these issues, we propose a fuzzy rule-based faulty node classification and management scheme for WSNs that can detect and reuse faulty sensor nodes according to their fault status. In order to overcome uncertainties that are inherited in the WSN environment, a fuzzy logic based method is utilized. Fuzzy interface engine categorizes different nodes according to the chosen membership function and the defuzzifier generates a non-fuzzy control to retrieve the various types of nodes. In addition, we employed a routing scheme that reuses the retrieved faulty nodes during the data routing process. We performed extensive experiments on the proposed scheme using various network scenarios. The experimental results are compared with the existing algorithms to demonstrate the effectiveness of the proposed algorithm in terms of various important performance metrics.

[1]  Xiuzhen Cheng,et al.  Localized fault-tolerant event boundary detection in sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[2]  Sajal K. Das,et al.  Centralized and Clustered k-Coverage Protocols for Wireless Sensor Networks , 2012, IEEE Transactions on Computers.

[3]  Lucia Lo Bello,et al.  A novel approach for dynamic traffic lights management based on Wireless Sensor Networks and multiple fuzzy logic controllers , 2015, Expert Syst. Appl..

[4]  Aarti Jain,et al.  Eigenvector centrality based cluster size control in randomly deployed wireless sensor networks , 2015, Expert Syst. Appl..

[5]  Shahram Sarkani,et al.  A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier , 2012, Expert Syst. Appl..

[6]  Hafizur Rahaman,et al.  FFMS: Fuzzy Based Fault Management Scheme in Wireless Sensor Networks , 2012 .

[7]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[8]  Zhao-wei Qu,et al.  Efficient neighbor collaboration fault detection in WSN , 2011 .

[9]  Rajashekhar C. Biradar,et al.  Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach , 2013, J. Netw. Comput. Appl..

[10]  Tommy W. S. Chow,et al.  Probabilistic fault detector for Wireless Sensor Network , 2014, Expert Syst. Appl..

[11]  Thambipillai Srikanthan,et al.  Energy-efficient cluster-based scheme for failure management in sensor networks , 2008, IET Commun..

[12]  Alexis Papadimitriou,et al.  Edge betweenness centrality: A novel algorithm for QoS-based topology control over wireless sensor networks , 2012, J. Netw. Comput. Appl..

[13]  Ertan Onur,et al.  Lifetime extension for surveillance wireless sensor networks with intelligent redeployment , 2011, J. Netw. Comput. Appl..

[14]  Arun Somani,et al.  Distributed fault detection of wireless sensor networks , 2006, DIWANS '06.

[15]  Boubaker Daachi,et al.  Application of fuzzy inference systems to detection of faults in wireless sensor networks , 2012, Neurocomputing.

[16]  Bara'a Ali Attea,et al.  A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks , 2012, Appl. Soft Comput..

[17]  M. Merabti,et al.  A Cellular Approach to Fault Detection and Recovery in Wireless Sensor Networks , 2009, 2009 Third International Conference on Sensor Technologies and Applications.

[18]  Hafizur Rahaman,et al.  Effective fault detection and routing scheme for wireless sensor networks , 2014, Comput. Electr. Eng..

[19]  Cheng Li,et al.  An Agreement-Based Fault Detection Mechanism for Under Water Sensor Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[20]  Stefano Chessa,et al.  Comparison-based system-level fault diagnosis in ad hoc networks , 2001, Proceedings 20th IEEE Symposium on Reliable Distributed Systems.

[21]  Yoon-Hwa Choi,et al.  Fault detection of wireless sensor networks , 2008, Comput. Commun..

[22]  Hao Yuan,et al.  A Distributed Bayesian Algorithm for data fault detection in wireless sensor networks , 2015, 2015 International Conference on Information Networking (ICOIN).

[23]  G. Venkataraman,et al.  A Cluster-Based Approach to Fault Detection and Recovery in Wireless Sensor Networks , 2007, 2007 4th International Symposium on Wireless Communication Systems.