A Fuzzy-Based Simulation System for Controlling Sensor Speed in Wireless Sensor Networks

In Wireless Sensor Networks (WSN), cluster formation and cluster head selection are critical issues. They can drastically affect the network's performance in different environments with different characteristics. In order to deal with this problem, we have proposed a Fuzzy-based system for cluster-head selection and controlling sensor speed in Wireless Sensor Networks (WSNs). The proposed system is constructed by 2 Fuzzy Logic Controllers (FLC). We use 4 input linguistic parameters for evaluating cluster-head decision probability in FLC1. Then, we use the output of FLC1 and two other linguistic parameters as input parameters of FLC2 to control sensor speed. By considering the moving speed of the sensor we are able to predict whether the node will leave or stay in the cluster. In this paper, we evaluate FLC2 by simulations and show that it has a good behavior.

[1]  Leonard Barolli,et al.  A Fuzzy-Based Cluster-Head Selection System forWSNs Considering Different Parameters , 2012, 2012 26th International Conference on Advanced Information Networking and Applications Workshops.

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

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

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

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

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

[8]  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..

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

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

[11]  Leonard Barolli,et al.  A Fuzzy-Based Simulation System for Controlling Sensor Speed in Wireless Sensor Networks , 2012, 2012 15th International Conference on Network-Based Information Systems.

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

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

[14]  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).

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

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

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

[18]  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.

[19]  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.

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

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

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