With the explosion of data production, the efficiency of data management and analysis has been concerned by both industry and academia. Meanwhile, more and more energy is consumed by the IT infrastructure especially the larger scale distributed systems. In this paper, a novel idea for optimizing the Energy Consumption (EC for short) of MapReduce system is proposed. We argue that a fair data placement is helpful to save energy, and then we propose three goals of data placement, and a modulo based Data Placement Algorithm (DPA for short) which achieves these goals. Afterwards, the correctness of the proposed DPA is proved from both theoretical and experimental perspectives. Three different systems which implement MapReduce model with differen...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
The energy consumption of a data center and hence the carbon footprint from it largely depends on th...
This paper aims to quantitatively measure the impact of different data centers networking topologies...
International audienceWith the explosion of data production, the efficiency of data management and a...
The majority of large-scale data intensive applications carried out by information centers are based...
The majority of large-scale data intensive applications executed by data centers are based on MapRed...
Abstract—The majority of large-scale data intensive appli-cations executed by data centers are based...
With the recent emergence of cloud computing based services on the Inter-net, MapReduce and distribu...
The efficient use of energy is essential to address concerns of cost and sustainability. Many data c...
Abstract—The majority of large-scale data intensive applications executed by data centers are based ...
Worldwide data centers consume about 300 billion kWh of energy per year, which accounts for 2% of to...
Most common huge volume data processing programs do counting, sorting, merging etc. Such programs re...
In applications of MapReduce, Terasort is one of the most successful ones, which has helped Hadoop t...
The energy-performance optimization of datacenters becomes ever challenging, due to heterogeneous wo...
Abstract—MapReduce has become a popular framework for Big Data applications. While MapReduce has rec...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
The energy consumption of a data center and hence the carbon footprint from it largely depends on th...
This paper aims to quantitatively measure the impact of different data centers networking topologies...
International audienceWith the explosion of data production, the efficiency of data management and a...
The majority of large-scale data intensive applications carried out by information centers are based...
The majority of large-scale data intensive applications executed by data centers are based on MapRed...
Abstract—The majority of large-scale data intensive appli-cations executed by data centers are based...
With the recent emergence of cloud computing based services on the Inter-net, MapReduce and distribu...
The efficient use of energy is essential to address concerns of cost and sustainability. Many data c...
Abstract—The majority of large-scale data intensive applications executed by data centers are based ...
Worldwide data centers consume about 300 billion kWh of energy per year, which accounts for 2% of to...
Most common huge volume data processing programs do counting, sorting, merging etc. Such programs re...
In applications of MapReduce, Terasort is one of the most successful ones, which has helped Hadoop t...
The energy-performance optimization of datacenters becomes ever challenging, due to heterogeneous wo...
Abstract—MapReduce has become a popular framework for Big Data applications. While MapReduce has rec...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
The energy consumption of a data center and hence the carbon footprint from it largely depends on th...
This paper aims to quantitatively measure the impact of different data centers networking topologies...