Add to ORKGMy research centers around performance modeling, optimization and resource management for MapReduce workflows with completion time constrains. My work is motivated by (1) the popularity of MapReduce framework and its open source implementation Hadoop that provides an economically compelling alternative for efficient analytics over ”Big Data ” in the enterprise; and (2) the recent technological trend shift toward
Currently, Hadoop MapReduce framework has been applied to many productive fields to analyze big data...
Data intensive applications adopts Map Reduce as a major computing model. Hadoop, an open source imp...
Big Data such as Terabyte and Petabyte datasets are rapidly becoming the new norm for various organi...
Big Data analytics is increasingly performed using the MapReduce paradigm and its open-source implem...
Big Data analytics is increasingly performed using the MapReduce paradigm and its open-source implem...
MapReduce framework has become the state-of-the-art paradigm for large-scale data processing. In our...
Part 4: Green Computing and Resource ManagementInternational audienceMany companies are increasingly...
In the recent years, large-scale data analysis has become critical to the success of modern enterpri...
There is an increasing number of MapReduce applications, e.g., personalized advertising, spam detect...
Several companies are increasingly using MapReduce for efficient large scale data processing such as...
In the recent years, large-scale data analysis has become critical to the success of modern enterpri...
In recent years there has been an extraordinary growth of large-scale data processing and related te...
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University...
Nowadays MapReduce and its open source implementation, Apache Hadoop, are the most widespread soluti...
Scalable by design to very large computing systems such as grids and clouds, MapReduce is currently ...
Currently, Hadoop MapReduce framework has been applied to many productive fields to analyze big data...
Data intensive applications adopts Map Reduce as a major computing model. Hadoop, an open source imp...
Big Data such as Terabyte and Petabyte datasets are rapidly becoming the new norm for various organi...
Big Data analytics is increasingly performed using the MapReduce paradigm and its open-source implem...
Big Data analytics is increasingly performed using the MapReduce paradigm and its open-source implem...
MapReduce framework has become the state-of-the-art paradigm for large-scale data processing. In our...
Part 4: Green Computing and Resource ManagementInternational audienceMany companies are increasingly...
In the recent years, large-scale data analysis has become critical to the success of modern enterpri...
There is an increasing number of MapReduce applications, e.g., personalized advertising, spam detect...
Several companies are increasingly using MapReduce for efficient large scale data processing such as...
In the recent years, large-scale data analysis has become critical to the success of modern enterpri...
In recent years there has been an extraordinary growth of large-scale data processing and related te...
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University...
Nowadays MapReduce and its open source implementation, Apache Hadoop, are the most widespread soluti...
Scalable by design to very large computing systems such as grids and clouds, MapReduce is currently ...
Currently, Hadoop MapReduce framework has been applied to many productive fields to analyze big data...
Data intensive applications adopts Map Reduce as a major computing model. Hadoop, an open source imp...
Big Data such as Terabyte and Petabyte datasets are rapidly becoming the new norm for various organi...