Affordable Cluster-Based Context for Multimedia Big Data Extraction
Pampati Nagaraju1, Etyala Ajith Kumar2
1Pampati Nagaraju, Department of Computer Science and Engineering, Balaji Institute of Technology & Science, Warangal (Telangana), India.
2Etyala Ajith Kumar, Department of Computer Science and Engineering, Talla Padmavathi College of Engineering, Kazipet, Warangal (Telangana), India.
Manuscript received on 25 February 2020 | Revised Manuscript received on 05 March 2020 | Manuscript Published on 15 March 2020 | PP: 49-52 | Volume-9 Issue-4S2 March 2020 | Retrieval Number: D10120394S220/2020©BEIESP | DOI: 10.35940/ijitee.D1012.0394S220
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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: Most of the data being created than ever before and that can be textual, multimedia, spatial information. To process this data, several data processing platforms have been developed including Hadoop, based on the Map Reduce model and HPCC systems. The HPCC System analysis provides a framework for multimedia data processing. Moreover, Multimedia data encompasses a wide variety of data which is not limited to image data, video data, audio data and even textual data, while developing a unified framework for such wide variety of data to consider computational difficulty in it. Preliminary results show that HPCC can potentially reduce the computational complexity significantly.
Keywords: Hadoop Big Data Analysis, HPCC framework, HDFS, Feature Extraction, Multimedia Big Data.
Scope of the Article: Big Data Security