An intelligent fuzzy-based cluster head selection system for wireless sensor networks and its performance evaluation

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hdl:2117/124828
Document typeConference report
Defense date2010
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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Abstract
Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network's communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In our previous work, in order to deal with this problem, we proposed a power reduction algorithm for sensor networks based on fuzzy logic and number of neighbor nodes. We call this algorithm F3N. In this paper, we implement a simulation system for clustering algorithms in sensor networks. We evaluate LEACH and F3N by some simulation results. Presently, we have implemented LEACH algorithm in NS-2. However, F3N is implemented in MATLAB. We are working to implement also F3N system in NS-2 in order to compare their performance.
CitationAndo, H., Barolli, L., Durresi, A., Xhafa, F., Koyama, A. An intelligent fuzzy-based cluster head selection system for wireless sensor networks and its performance evaluation. A: International Conference on Network-Based Information Systems. "The 13th International Conference on Network-Based Information Systems, NBiS 2010, 14-16 September 2010, Takayama, Gifu, Japan: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 55-61.
ISBN978-0-7695-4167-9
Publisher versionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5635710
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