MCEEP-BDA: Multilevel Clustering Based -Energy Efficient Privacy-Preserving Big Data Aggregation in Large-Scale Wsn
Dhanapal.R1, Selva Pandian. D2, Karthik.S3
1Dhanapal.R, Assistant Professor, Department of Computer Science Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India.
2Selva Pandian. D, Assistant Professor, Department of Computer Science Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India.
3Karthik .S, Professor & Dean, Department of Computer Science and Engineering, SNS College of Technology, Coimbatore, Tamilnadu, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 6779-6785 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2977109119/2019©BEIESP | DOI: 10.35940/ijeat.A2977.109119
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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 current scenario, the Big Data processing that includes data storage, aggregation, transmission and evaluation has attained more attraction from researchers, since there is an enormous data produced by the sensing nodes of large-scale Wireless Sensor Networks (WSNs). Concerning the energy efficiency and the privacy conservation needs of WSNs in big data aggregation and processing, this paper develops a novel model called Multilevel Clustering based- Energy Efficient Privacy-preserving Big Data Aggregation (MCEEP-BDA). Initially, based on the pre-defined structure of gradient topology, the sensor nodes are framed into clusters. Further, the sensed information collected from each sensor node is altered with respect to the privacy preserving model obtained from their corresponding sinks. The Energy model has been defined for determining the efficient energy consumption in the overall process of big data aggregation in WSN. Moreover, Cluster_ head Rotation process has been incorporated for effectively reducing the communication overhead and computational cost. Additionally, algorithm has been framed for Least BDA Tree for aggregating the big sensor data through the selected cluster heads effectively. The simulation results show that the developed MCEEP-BDA model is more scalable and energy efficient. And, it shows that the Big Data Aggregation (BDA) has been performed here with reduced resource utilization and secure manner by the privacy preserving model, further satisfying the security concerns of the developing application-oriented needs.
Keywords: Wireless Sensor Network (WSN), Big Data Aggregation (BDA), Energy Efficiency, Privacy Preserving, Cluster_head Rotation and Least BDA Tree.