MapReduce has become a popular high performance computing paradigm for large-scale data processing. Hadoop, an open source implementation of MapReduce, has been widely deployed in large clusters containing thousands of machines by companies such as Yahoo! and Facebook to support batch processing for large jobs submitted from multiple users (i.e., MapReduce workloads). However, there are certainly a lot of room to improve the performance and fairness of Hadoop. In this thesis, we focus on optimization techniques on job scheduling and resource allocation to improve the performance and fairness of Hadoop system. First, we focus on the performance optimization for MapReduce workloads under FIFO scheduler without changing the source code of Hado...
With the development of electronic devices, more and more mobile clients are connected to the Intern...
In this paper, we explore the feasibility of enabling the scheduling of mixed hard and soft real-tim...
Nowadays, data-intensive problems are so prevalent that numerous organizations in various industries...
MapReduce has become a popular high performance computing paradigm for large-scale data processing. ...
In present day scenario cloud has become an inevitable need for majority of IT operational organizat...
Cloud computing is a power platform to deal with big data. Among several software frameworks used fo...
For large scale parallel applications Mapreduce is a widely used programming model. Mapreduce is an ...
The MapReduce framework has become the defacto scheme for scalable semi-structured and un-structured...
MapReduce is an emerging paradigm for data intensive processing with support of cloud computing tech...
MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and d...
Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses Hadoop Di...
Cloud computing has emerged as a model that harnesses massive capacities of data centers to host ser...
Resource allocation and scheduling on clouds are required to harness the power of the underlying res...
AbSTRACT Hadoop-MapReduce is one of the dominant parallel data processing tool designed for large sc...
Abstract — The specific choice of workload task schedulers for Hadoop MapReduce applications can hav...
With the development of electronic devices, more and more mobile clients are connected to the Intern...
In this paper, we explore the feasibility of enabling the scheduling of mixed hard and soft real-tim...
Nowadays, data-intensive problems are so prevalent that numerous organizations in various industries...
MapReduce has become a popular high performance computing paradigm for large-scale data processing. ...
In present day scenario cloud has become an inevitable need for majority of IT operational organizat...
Cloud computing is a power platform to deal with big data. Among several software frameworks used fo...
For large scale parallel applications Mapreduce is a widely used programming model. Mapreduce is an ...
The MapReduce framework has become the defacto scheme for scalable semi-structured and un-structured...
MapReduce is an emerging paradigm for data intensive processing with support of cloud computing tech...
MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and d...
Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses Hadoop Di...
Cloud computing has emerged as a model that harnesses massive capacities of data centers to host ser...
Resource allocation and scheduling on clouds are required to harness the power of the underlying res...
AbSTRACT Hadoop-MapReduce is one of the dominant parallel data processing tool designed for large sc...
Abstract — The specific choice of workload task schedulers for Hadoop MapReduce applications can hav...
With the development of electronic devices, more and more mobile clients are connected to the Intern...
In this paper, we explore the feasibility of enabling the scheduling of mixed hard and soft real-tim...
Nowadays, data-intensive problems are so prevalent that numerous organizations in various industries...