Title :
Analysis on enhancing storm to efficiently process big data in real time
Author :
Nivash, J.P. ; Deni Raj, Ebin ; Dhinesh Babu, L.D. ; Nirmala, M. ; Manoj, Kumar V.
Author_Institution :
Sch. of Inf. Technol. & Eng., VIT Univ., Vellore, India
Abstract :
The rapid growth of huge data has become a challenge to the data analysts in recent time. As the data is growing exponentially many techniques are on the rise, for processing the real time data. Many data processing models like Hadoop, Apache YARN, Mapreduce, Storm, and Akka are leading the Big Data domain. This paper analyses and compares all the data processing models stated above. Researchers are trying to increase the efficiency of the algorithms used in the data processing. In this paper, we propose two algorithms namely JATS and SD, which will enhance the efficiency of the storm data processing architecture.
Keywords :
Big Data; data analysis; distributed processing; Akka; Apache YARN; Big data domain; Hadoop; JATS; Mapreduce; SD; Storm data processing architecture; data analysts; data processing models; Algorithm design and analysis; Data models; Data processing; Fasteners; Real-time systems; Storms; Topology; Apache Storm; Bigdata; Hadoop; Real time data processing;
Conference_Titel :
Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on
Print_ISBN :
978-1-4799-2695-4
DOI :
10.1109/ICCCNT.2014.7093076