Efficient cluster head selection using Naïve Bayes classifier for wireless sensor networks

Data mining and approaches based on it have always been of approaches that have been considered in solving problems in the field of computer, but on some issues, this approach has been neglected. The area of wireless sensor networks and specifically the issue of optimal determining of the cluster head node are of these issues. To solve the problem of optimal determining of the cluster head node, Naïve Bayes that is the subset of data mining techniques is used in this paper. The results obtained after simulation of the presented algorithm show that the efficiency of this algorithm is significantly higher compared with other approaches that have so far been used to solve this problem, and thus it can be said that using this algorithm will lead to improved outcomes of solving this problem.

[1]  Athanasios V. Vasilakos,et al.  Data Mining for the Internet of Things: Literature Review and Challenges , 2015, Int. J. Distributed Sens. Networks.

[2]  Athanasios V. Vasilakos,et al.  Cross-Layer Support for Energy Efficient Routing in Wireless Sensor Networks , 2009, J. Sensors.

[3]  Athanasios V. Vasilakos,et al.  A survey on trust management for Internet of Things , 2014, J. Netw. Comput. Appl..

[4]  Athanasios V. Vasilakos,et al.  Directional routing and scheduling for green vehicular delay tolerant networks , 2012, Wireless Networks.

[5]  G. Ahmed,et al.  Cluster head selection using decision trees for Wireless Sensor Networks , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[6]  Selim Bayrakli,et al.  Genetic Algorithm Based Energy Efficient Clusters (GABEEC) in Wireless Sensor Networks , 2012, ANT/MobiWIS.

[7]  Naixue Xiong,et al.  Context-Aware Middleware for Multimedia Services in Heterogeneous Networks , 2010, IEEE Intelligent Systems.

[8]  Seon-Ho Park,et al.  CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks , 2008, 2008 10th International Conference on Advanced Communication Technology.

[9]  Athanasios V. Vasilakos,et al.  Hierarchical Data Aggregation Using Compressive Sensing (HDACS) in WSNs , 2015, ACM Trans. Sens. Networks.

[10]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[11]  Ping Zhang,et al.  Cluster Head Selection Using Analytical Hierarchy Process for Wireless Sensor Networks , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[12]  Fatos Xhafa,et al.  A Fuzzy-Based Simulation System for Cluster-Head Selection and Sensor Speed Control in Wireless Sensor Networks , 2012, 2012 Third International Conference on Emerging Intelligent Data and Web Technologies.

[13]  Athanasios V. Vasilakos,et al.  Local Area Prediction-Based Mobile Target Tracking in Wireless Sensor Networks , 2015, IEEE Transactions on Computers.

[14]  Athanasios V. Vasilakos,et al.  Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter , 2011, Comput. Commun..

[15]  Athanasios V. Vasilakos,et al.  Security of the Internet of Things: perspectives and challenges , 2014, Wireless Networks.

[16]  Jin-Shyan Lee,et al.  Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication , 2012, IEEE Sensors Journal.

[17]  Athanasios V. Vasilakos,et al.  Compressed data aggregation for energy efficient wireless sensor networks , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[18]  S. Hussain,et al.  Genetic Algorithm for Energy Efficient Clusters in Wireless Sensor Networks , 2007, Fourth International Conference on Information Technology (ITNG'07).

[19]  Shusen Yang,et al.  A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities , 2013, IEEE Wireless Communications.

[20]  Athanasios V. Vasilakos,et al.  Backpressure-based routing protocol for DTNs , 2010, SIGCOMM '10.

[21]  Vidushi Sharma,et al.  Cluster Head Selection in Wireless Sensor Networks under Fuzzy Environment , 2013 .

[22]  Athanasios V. Vasilakos,et al.  Information centric network: Research challenges and opportunities , 2015, J. Netw. Comput. Appl..

[23]  Witold Pedrycz,et al.  An Evolutionary Multiobjective Sleep-Scheduling Scheme for Differentiated Coverage in Wireless Sensor Networks , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[24]  Athanasios V. Vasilakos,et al.  CDC: Compressive Data Collection for Wireless Sensor Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[25]  Yong Wang,et al.  An Ant Colony Clustering Routing Algorithm for Wireless Sensor Networks , 2009, 2009 Third International Conference on Genetic and Evolutionary Computing.

[26]  Athanasios V. Vasilakos,et al.  Spatial Reusability-Aware Routing in Multi-Hop Wireless Networks , 2016, IEEE Transactions on Computers.

[27]  Naixue Xiong,et al.  Multi-layer clustering routing algorithm for wireless vehicular sensor networks , 2010, IET Commun..

[28]  Athanasios V. Vasilakos,et al.  Algorithm design for data communications in duty-cycled wireless sensor networks: A survey , 2013, IEEE Communications Magazine.

[29]  Athanasios V. Vasilakos,et al.  EDAL: An Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection Protocol for Wireless Sensor Networks , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[30]  Neng-Chung Wang,et al.  Efficient Cluster Head Selection Methods for Wireless Sensor Networks , 2010, J. Networks.

[31]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[32]  Athanasios V. Vasilakos,et al.  Approximating Congestion + Dilation in Networks via "Quality of Routing" Games , 2012, IEEE Trans. Computers.

[33]  Athanasios V. Vasilakos,et al.  Reliable Multicast with Pipelined Network Coding Using Opportunistic Feeding and Routing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[34]  Shen Lianfeng,et al.  NEAR OPTIMAL CLUSTER-HEAD SELECTION FOR WIRELESS SENSOR NETWORKS , 2007 .

[35]  Mo Li,et al.  A Survey on Topology Control in Wireless Sensor Networks: Taxonomy, Comparative Study, and Open Issues , 2013, Proc. IEEE.

[36]  Athanasios V. Vasilakos,et al.  EDAL: An Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection Protocol for Heterogeneous Wireless Sensor Networks , 2015, IEEE/ACM Transactions on Networking.

[37]  Yue Zhang,et al.  Interference-Based Topology Control Algorithm for Delay-Constrained Mobile Ad Hoc Networks , 2015, IEEE Transactions on Mobile Computing.

[38]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[39]  Athanasios V. Vasilakos,et al.  Tight Performance Bounds of Multihop Fair Access for MAC Protocols in Wireless Sensor Networks and Underwater Sensor Networks , 2012, IEEE Transactions on Mobile Computing.

[40]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[41]  Kasmiran Jumari,et al.  Cluster - Head selection by remaining energy consideration in a wireless sensor network , 2011 .