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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 2, 2016.
Abstract: In this research an efficient data gathering scheme is presented using mobile sink as data collector with Clustering as sensor organizer in a randomly organized sensors in sensing field for wireless sensor network. The scheme not only extends the network lifetime through clustering process but also improves the data gathering mechanism through efficient and simplified mobile sink movement scheme. The cluster heads selection is based on both energy and data weight, which gathering all the data from the nodes within a cluster and then delivers it to the sink. The single mobile sink which visits the cluster heads as per defined path gathers data periodically. The scheme is organized through “Mobile Sink based Data Gathering Protocol (MSDGP)” which combines single message energy efficient clustering and data gathering process. For performance evaluation, the protocol is extensively simulated for different performance metrics, namely Residual energy consumption, Number of dead nodes during variable number of rounds and Network lifetime. The results proves that MSDGP is successful in achieving the defined objectives of energy efficiency and is capable of extending the network lifetime by increasing the number of rounds. Therefore, proposed protocol is more suitable for scenarios where sensor nodes generate variable amount of data.
Muhammad Ali Khan, Arif Iqbal Umar, Babar Nazir, Noor ul Amin, Shaukat Mehmood and Kaleem Habib, “Energy Efficient Clustering Using Fixed Sink Mobility for Wireless Sensor Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 7(2), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070266
@article{Khan2016,
title = {Energy Efficient Clustering Using Fixed Sink Mobility for Wireless Sensor Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070266},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070266},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {2},
author = {Muhammad Ali Khan and Arif Iqbal Umar and Babar Nazir and Noor ul Amin and Shaukat Mehmood and Kaleem Habib}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.