An Integrated Fuzzy-Based System for Cluster-Head Selection and Sensor Speed Control in Wireless Sensor Networks

Cluster formation and cluster head selection are important problems in Wireless Sensor Network WSN applications and can drastically affect the network's communication energy dissipation. However, selecting the cluster head is not easy in different environments which may have different characteristics. In order to deal with this problem, in this paper, we implement an integrated fuzzy-based system for controlling sensor speed in WSNs. Different from our previous work, we consider 4 input linguistic parameters: Remaining Power of Sensor RPS, Degree of Number of Neighbor Nodes D3N, Distance from Cluster Centroid DCC and Sensor Speed SS for selection of the cluster-head and the control of sensor speed. By controlling the sensor speed, we are able to predict whether the node will leave or stay in the cluster. We evaluate the proposed system by simulations and show that the system has a good behavior.

[1]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[2]  Adrian Perrig,et al.  ACE: An Emergent Algorithm for Highly Uniform Cluster Formation , 2004, EWSN.

[3]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[4]  L. Barolli,et al.  A cluster head selection method for wireless sensor networks based on fuzzy logic , 2007, TENCON 2007 - 2007 IEEE Region 10 Conference.

[5]  Samir Khuller,et al.  A clustering scheme for hierarchical control in multi-hop wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[6]  L. Barolli,et al.  A cluster head decision system for sensor networks using fuzzy logic and number of neighbor nodes , 2008, 2008 First IEEE International Conference on Ubi-Media Computing.

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

[8]  Girdhari Singh,et al.  SCHS: Smart Cluster Head Selection Scheme for Clustering Algorithms in Wireless Sensor Networks , 2012 .

[9]  Ian F. Akyildiz,et al.  Wireless sensor and actor networks: research challenges , 2004, Ad Hoc Networks.

[10]  Tatsuya Omori,et al.  Time Domain Replica Signal Based Interference Compensation for SP-MIMO/OFDM with Large Delay Spread Channel , 2014, Int. J. Distributed Syst. Technol..

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

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

[13]  Catherine Rosenberg,et al.  Topics in ad hoc and sensor networks , 2006, IEEE Commun. Mag..

[14]  J. Mendel Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[15]  Krishna M. Sivalingam,et al.  Data Gathering Algorithms in Sensor Networks Using Energy Metrics , 2002, IEEE Trans. Parallel Distributed Syst..

[16]  Leonard Barolli,et al.  GAMAN: A GA Based QoS Routing Method for Mobile Ad-Hoc Networks , 2003, J. Interconnect. Networks.

[17]  Frank Leymann,et al.  Making Scientific Applications on the Grid Reliable Through Flexibility Approaches Borrowed from Service Compositions , 2010 .

[18]  Stefano Basagni,et al.  Distributed clustering for ad hoc networks , 1999, Proceedings Fourth International Symposium on Parallel Architectures, Algorithms, and Networks (I-SPAN'99).

[19]  Lui Sha,et al.  Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks , 2004, IEEE Trans. Mob. Comput..

[20]  Emmanuel Udoh Evolving Developments in Grid and Cloud Computing: Advancing Research , 2012 .

[21]  Leonard Barolli,et al.  Implementation and Evaluation of A Fuzzy-based Cluster-Head Selection System for Wireless Sensor Networks Considering Network Traffic , 2015, J. Mobile Multimedia.

[22]  Qilian Liang,et al.  A design methodology for wireless personal area networks with power efficiency , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[23]  Ravi Prakash,et al.  Max-min d-cluster formation in wireless ad hoc networks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[24]  Ray E. Sheriff,et al.  Mobility management incorporating fuzzy logic for a heterogeneous IP environment , 2001, IEEE Commun. Mag..

[25]  Leonard Barolli,et al.  F3N: An Intelligent Fuzzy-Based Cluster Head Selection System for WSNs and Its Performance Evaluation , 2015, Int. J. Distributed Syst. Technol..

[26]  Fatos Xhafa,et al.  Performance evaluation of two fuzzy-based cluster head selection systems for wireless sensor networks , 2008, Mob. Inf. Syst..