Cluster Head Selection and Packet Delivery Estimation Based on K-Means and FCM
Anil Khandelwal1, Yogendra Kumar Jain2
1Anil Khandelwal, Research Scholar, Electronics & Communication, RGPV Bhopal, MP, India.
2Yogendra Kumar Jain, Associate Professor Department of Electronics and Instrumentation Engineering, SATI Vidisha, MP, India.

Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 10028-10036 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9231118419/2019©BEIESP | DOI: 10.35940/ijrte.D9231.118419

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Abstract: In this paper comparative study have been presented for the efficient cluster head selection based on k-means and fuzzy c-means (FCM) clustering algorithms. It is observed that the nodes assignment after the clustering is different through k-means and FCM. It is because of the variant initialization mechanism of the k-means and FCM. But the assignment of cluster does not affect the results. It is clearly depicted from the packet delivery time results by our approach. It shows that the k-means and FCM have the capability of CHs selection in the required time frame and it shows the effectiveness in different iterations also. When aggregate packet delivery has been considered the same situation has been observed which depicts the capability of our approach. K-means found to be faster in comparison to FCM.
Keywords: WSN, CHs, K-means, FCM, SAW and WPM.
Scope of the Article: Web-Based Learning: Innovation and Challenges.