A Framework of Security and Performance Enhancement for Hadoop
Adhishtha Tyagi, Sonia Sharma · International Journal of Advanced Research in Computer Science and Software Engineering · 2017
Hadoop framework has been emerged as the most effective and widely adopted framework for Big Data processing. Map Reduce programming model is used for processing as well as generating large data sets. Data security has become an important issue as far as storage is concerned. By default theres no security mechanism in hadoop and it is the first choice of the business analyst and industrialists to store and manage data as well as theres a need to introduce security solutions to Hadoop in order to secure the important data in the Hadoop environment. We implemented and evaluated Dynamic Task Splitting Scheduler (DTSS) which explores the tradeoffs between fairness and data performance by splitting the tasks dynamically before processing in hadoop along with AES-MR (an Advanced Encryption Standard based encryption using mapreduce) encryption in MapReduce paradigm. This paper would be useful for beginners and researchers for understanding DTSS scheduling along with security.