Time-Efficient Advent for Diagnosing Flaws in Hadoop on the Big Sensor Type Data
Hadoop is a MapReduce-based distributed processing framework used in the area of big data analytics in every organizations. Big sensor data is difficult to manage with the traditional data management tools. Thus, Hadoop challenges to manage it in high scalable amount in a time-efficient manner. In this paper, for fast detection of flaws in big sensor data sets, a different type of approach in diagnosing flaws with the time efficiency is used. Due to the wireless transfer of data across the nodes in a wireless sensor networks, there can be loss of data which will result in wrong interpretation of data at the nodes. The proposed approach of this paper is to form a group of sensors as a cluster. If any sensor detects violations, then the energy of that sensor has to be compared with the other sensors. The sensor having the highest energy will become the cluster head, and it will send the sensed data to the data center. The data center then diagnoses the flaw with respect to the sensed data in the big sensor data.
KeywordsHDFS Hadoop MapReduce Big sensor data
- 1.Chi Yang, Chang Liu, Xuyun Zhang, Surya Nepal, and Jinjun Chen: A Time Efficient Approach for Detecting Errors in Big Sensor Data on Cloud. In: IEEE Transactions on Parallel And Distributed Systems, Vol. 26, No. 2, February 2015.Google Scholar
- 2.Detecting Forest Fires using Wireless Sensor Networks, http://www.libelium.com/wireless_sensor_networks_to_detec_forest_fires/.
- 3.Kechar Bouabdellah, Houache Noureddine, and Sekhri Larbi: Using Wireless Sensor Networks for Reliable Forest Fires Detection. In: Procedia Computer Science, Vol. 19, 2013, Pages 794–801.Google Scholar
- 4.Lidice Garcia Rios, and Jos’e Alberto Incera Diguez: Big Data Infrastructure for analyzing data generated by Wireless Sensor Networks. In: IEEE International Congress on Big Data, 2014–06, Pages 816–823.Google Scholar
- 5.Subhash Chandra, and Deepak Motwani: An Approach to Enhance the Performance of Hadoop MapReduce Framework for Big Data. In: International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE), 2016.Google Scholar
- 6.In-Yong Jung, Ki-Hyun Kim, Byong-John Han, and Chang-Sung Jeong: Hadoop-Based Distributed Sensor Node Management System. In: International Journal of Distributed Sensor Networks, Vol. 10, 2014.Google Scholar
- 7.Parth Gohil, Bakul Panchal, and J. S. Dhobi: A novel approach to improve the performance of Hadoop in handling of small files. In: IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2015.Google Scholar
- 8.Maneesha V. Ramesh: Real-Time Wireless Sensor Network for Landslide Detection. In: Third International Conference on Sensor Technologies and Applications, 2009. SENSORCOMM ’09.Google Scholar
- 9.Sethuraman Rao, G. K. Nithya, and K Rakesh: Development of a wireless sensor network for detecting fire and Gas leaks in a collapsing building. In: International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2014.Google Scholar
- 10.Saravanan S, and B. Uma Maheswari: Analyzing Large Web Log Files in a Hadoop Distributed Cluster Environment. In: International Journal of Computer Technology and Applications (IJCTA), Vol. 5, Issue 5, (2014).Google Scholar
- 11.Rahul, P. K., and K.T. Gireesh: A Novel Authentication Framework for Hadoop. In: Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 1, Springer India, Number 324, New Delhi, Pages 333340 (2015).Google Scholar
- 12.Sabrina Boubiche, Djallel Eddine Boubiche, and Bilami Azzedine: Integrating Big data paradigm in WSNs. In: International Conference on Big Data and Advanced Wireless Technologies, Article No. 56, 2016.Google Scholar