Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

WSNs have many applications in modern life. Thus, optimization of the network operation is required to maximize its lifetime. The energy is a major issue in order to increase the lifetime of WSNs. The clustering algorithm is one of the proposed algorithms to enhance the lifetime of WSNs. The operation of the clustering algorithm is divided into cluster heads CHs selection and cluster formation. However, most of the previous works have focused on CHs selection, and have not considered the cluster formation process, which is the important issue in clustering algorithm based routing schemes, and it can drastically affect the lifetime of WSNs. In this paper, a Fuzzy Logic based Clustering Algorithm for WSN CAFL has been proposed to improve the lifetime of WSNs. This approach uses fuzzy logic for CHs selection and clusters formation processes by using residual energy and closeness to the sink as fuzzy inputs in terms of CH selection, and residual energy of CH and closeness to CHs as fuzzy inputs in terms of clusters formation. Simulation results justify its efficiency.

[1]  Halil Yetgin,et al.  A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks , 2017, IEEE Communications Surveys & Tutorials.

[2]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[3]  Ganesh K. Venayagamoorthy,et al.  Computational Intelligence in Wireless Sensor Networks: A Survey , 2011, IEEE Communications Surveys & Tutorials.

[4]  Huazhong Zhang,et al.  IMPROVING ON LEACH PROTOCOL OF WIRELESS SENSOR NETWORKS USING FUZZY LOGIC , 2010 .

[5]  Timothy J. Shepard A channel access scheme for large dense packet radio networks , 1996, SIGCOMM 1996.

[6]  Cunqing Hua,et al.  Optimal Routing and Data Aggregation for Maximizing Lifetime of Wireless Sensor Networks , 2008, IEEE/ACM Transactions on Networking.

[7]  Barnabás Bede,et al.  Mathematics of Fuzzy Sets and Fuzzy Logic , 2012, Studies in Fuzziness and Soft Computing.

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

[9]  Haibo Zhang,et al.  Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.

[10]  Alyani Ismail,et al.  A survey on energy awareness mechanisms in routing protocols for wireless sensor networks using optimization methods , 2014, Trans. Emerg. Telecommun. Technol..

[11]  Abdellah Najid,et al.  Sefp: A New Routing Approach Using Fuzzy Logic For Clustered Heterogeneous Wireless Sensor Networks , 2015 .

[12]  Tom Francke,et al.  Innovative Applications and Developments of Micro-Pattern Gaseous Detectors , 2014 .

[13]  Azer Bestavros,et al.  SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks , 2004 .

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

[15]  H. Zhou,et al.  A Method for Deriving the Analytical Structure of a Broad Class of Typical Interval Type-2 Mamdani Fuzzy Controllers , 2013, IEEE Transactions on Fuzzy Systems.

[16]  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.

[17]  Li Qing,et al.  Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks , 2006, Comput. Commun..

[18]  Konstantinos Oikonomou,et al.  Braided Routing Technique to Balance Traffic Load in Wireless Sensor Networks , 2016, Int. J. Monit. Surveillance Technol. Res..

[19]  Indranil Gupta,et al.  Cluster-head election using fuzzy logic for wireless sensor networks , 2005, 3rd Annual Communication Networks and Services Research Conference (CNSR'05).

[20]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[21]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[22]  Abdellah Najid,et al.  (SET) Smart Energy Management and Throughput Maximization: A New Routing Protocol for WSNs , 2017 .

[23]  Omar Banimelhem,et al.  Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol , 2015, Int. J. Fuzzy Syst. Appl..

[24]  Jie Zhang,et al.  A General Self-Organized Tree-Based Energy-Balance Routing Protocol for Wireless Sensor Network , 2012, IEEE Transactions on Nuclear Science.

[25]  Abdellah Najid,et al.  CFFL: Cluster formation using fuzzy logic for wireless sensor networks , 2015, 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA).

[26]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[27]  Padmalaya Nayak,et al.  A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime , 2016, IEEE Sensors Journal.

[28]  José del Sagrado Martínez,et al.  A Bayesian Network for Predicting the Need for a Requirements Review , 2010 .