Storage and Retrieval of Data for Smart City using Hadoop
|International Journal of Computer Science and Engineering|
|© 2016 by SSRG - IJCSE Journal|
|Volume 3 Issue 5|
|Year of Publication : 2016|
|Authors : Ravi Gehlot|
How to Cite?
Ravi Gehlot, "Storage and Retrieval of Data for Smart City using Hadoop," SSRG International Journal of Computer Science and Engineering , vol. 3, no. 5, pp. 85-89, 2016. Crossref, https://doi.org/10.14445/23488387/IJCSE-V3I5P117
Smart cities are equipped with a huge range of technologies that generate enormous amount of data. Ubiquitous technologies that are embedded with Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) that frequently generates data. These devices are implanted everywhere in a smart city. The data generated by the sensors will grow so large, that it cannot be handled by the conventional File Storage Systems. Processing and analyzing of this amount of data needs special tasks to be done. For this we would require a special system that would store and process it with a feasible cost. Hadoop uses Hadoop Distributed File System (HDFS) to store data in distributed servers and MapReduce Algorithm to analyze and process the data. HDFS stores the stream of Application data in Data Nodes, which are mapped by NameNodes. This results in high availability and fault tolerant system. MapReduce algorithm uses key and value pair which makes the analyzing task easier.
Hadoop; Hadoop Distributed File System (HDFS); MapReduce; NameNode; DataNode; Big Data
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