Energy Efficient Clustering using MMHC (Modified Multi-Hop Clustering)
Vimala M1, Rajeev Ranjan2
1Vimala M*, Assistant Professor at Department of Computer Science, University of Agriculture Sciences, and Bangalore.
2Dr. Rajeev Ranjan, Associate Professor in the School of Computer Science and Applications at REVA University, Bangalore, India.
Manuscript received on October 11, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 1383-1388 | Volume-9 Issue-1, November 2019. | Retrieval Number: A3912119119/2019©BEIESP L39091081219/2019©BEIESP | DOI: 10.35940/ijitee.L3909.119119
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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: In recent years, the WSN has been widely used for building the DSS (Decision Support System) for solving the realworld problem. Moreover, out of several fields, one of the interesting field that requires DSS is monitoring of agriculture environment. Nowadays, Monitoring agriculture environment has become one of the essential field. A smart WSN system is capable of collecting as well as processing the huge data by monitoring the soil conditions, weather situation and others. Hence, IoT (Internet of Things) is employed in order to enhance the productivity and efficiency in the agriculture sector. IoT integrates the various technology such as RFI (Radio Frequency Identification), cloud computing, end-user applications and middleware system. Hence, it is obvious to obtain the higher efficiency for DC (Data Collection). In this paper shared based algorithm known as MMHC (Modified Multi-Hop Clustering) is proposed , this algorithm has three stage i.e. assembling , coupling and removing the redundant nodes. In this modified more than one node can be selected in the other two stage and the more than one node can be removed in third stage, this in terms helps in achieving higher efficiency. Later in order to evaluate the algorithm and prove the efficiency of our proposed algorithm, Comparative analysis is done with the Leach protocol based on the several parameter and it clearly shows that our model outperforms the Existing i.e. Leach algorithm.
Keywords: Clustering, Shared Algorithm, MMHC, Wireless networks.
Scope of the Article: Clustering