论文信息 - Generalized Net of MapReduce Computational Model

Generalized Net of MapReduce Computational Model

The topic in the current research work is one of the Big data frameworks known as MapReduce paradigm. This is a programming model for parallel processing of large volumes of data in distributed environment. MapReduce is applied in the clusters of commodity machines. The workflow of the MapReduce computational model is constructed using the possibilities of Generalized nets. The Generaliezed net model which is presented allows us to observe and monitor the Mapreduce framework in detail.

[1] Donald. Miner,et al. MapReduce design patterns , 2012 .

[2] Sugata Sanyal,et al. Computational Intelligence for Big Data Analysis: Frontier Advances and Applications , 2015 .

[3] Geoffrey C. Fox,et al. Using Clouds for Technical Computing , 2012, High Performance Computing Workshop.

[4] Jemal H. Abawajy,et al. Big Data in Complex Systems: Challenges and Opportunities , 2015 .

[5] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[6] Robert Stackowiak,et al. Big Data and the Internet of Things , 2015, Apress.

[7] Cevriye Gencer,et al. Yesterday, Today and Tomorrow of Big Data , 2015 .

[8] Vignesh Prajapati,et al. Big Data Analytics with R and Hadoop , 2013 .

[9] Howard Gobioff,et al. The Google file system , 2003, SOSP '03.

[10] Panagiotis Chountas,et al. Generalized Net of the Process of Sequential Pattern Mining by Generalized Sequential Pattern Algorithm (GSP) , 2014, IEEE Conf. on Intelligent Systems.

[11] Sugata Sanyal,et al. Computational Intelligence for Big Data Analysis , 2015 .

[12] Dennis Broeders,et al. Exploring the Boundaries of Big Data , 2016 .