Energy Evaluation of Sensor Protocol based on AI Techniques using CRAWDAD Data
Mohit Mittal1, Lalit Kumar Saraswat2
1Mohit Mittal, Department of Information Science and Technology, Kyoto Sangyo University, Kyoto, Japan.
2Lalit Kumar Saraswat, Department of Computer Science and Engineering, Raj Kumar Goel Institute of Technology, Ghaziabad, India.
Manuscript received on 11 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript published on 30 July 2019 | PP: 2812-2815 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1606078219/19©BEIESP | DOI: 10.35940/ijrte.B1606.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless sensor networks (WSNs) are one of popular communication networks that have garnered most prominent research attention due to their flexibility to sense physical environment parameters and converts into signal form. Battery power is limitation of WSN i.e. network will alive till battery is available. The network lifetime of WSN can be improved by use of energy-efficient cluster-based routing algorithms. In this paper, a key idea is attempting to improvise the LEACH protocol with the help of various clustering techniques and develop improved protocol such as LEACH-K, LEACH-FUZZYC, and LEACH-SOM. Simulation results show that LEACH-FUZZYC outperforms as compare to LEACH, LEACH-K and LEACH-SOM.
Index Terms: LEACH, Clustering Techniques, K-Means, Neural Network, Fuzzy C-Means.
Scope of the Article: Fuzzy Logics