Internet of things based smart community design and planning using hadoop-based big data analytics

Abstract

The current spreading out in big data is offering a hefty invention potential in itinerary of the fresh epoch of smart community. The foremost endeavor of smart community is to competently employ the asset of Big Data to manage and determine the issues face by recent smart cities for enhanced decision making. The applications of smart city fabricate a gigantic number of data that compose Big Data. This research proposes Big Data analytics architecture to address the challenges in Big Data analytics using Hadoop framework. The proposed framework is dealing particularly with data loading and processing. The proposal is consist of two parts that are Big Data loading (storage) in Hadoop file system and Big Data computation. The first part is liable for transferring Big Data from outer world and storing in Hadoop. The second part of the research deals with the data processing. YARN-based cluster management solution is provided to manage the cluster resource and process the data using Map-Reduce algorithm separately unlike traditional MapReduce architecture. The proposed architecture is tested with a variety of reliable datasets using Hadoop framework to verify and expose that the architecture offers precious imminent into the society organizations for development to improve the existing smart city architecture.