Add to ORKGRunning multiple instantiations of the MapReduce frame- work (MR-clusters) concurrently in a multicluster system or data center enables workload and data isolation, which is at- tractive for many organizations. We provision MR-clusters such that they receive equal levels of service by assigning each such cluster a dynamically changing weight that indi- cates its fair share of the resources
This research proposes a novel runtime system, Habanero Hadoop, to tackle the inefficient utilizatio...
Large quantities of data have been generated from multiple sources at exponential rates in the last ...
Compute clusters, consisting of many, uniformly built nodes, are used to run a large spectrum of dif...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
In many clusters and data centers, application frameworks are used that offer programming models suc...
Part 4: Green Computing and Resource ManagementInternational audienceWe present a resource-aware sch...
Today, resource capacity is no longer an issue for running large-scale distributed systems, such as ...
Adaptive workloads can change on–the–fly the configuration of their jobs, in terms of number of proc...
Due to the diversity in the applications that run in large distributed environments, many different ...
The cloud computing paradigm is realized through large scale distributed resource manage-ment and co...
Resource capacity is often over provisioned to primarily deal with short periods of peak load. Shapi...
In order to execute high performance applications on a cluster, it is highly desirable to provide di...
Dynamic resource provisioning, as an important data center software building block, helps to achieve...
As distributed computing systems are used more widely, driven by trends such as 'big data' and cloud...
This research proposes a novel runtime system, Habanero Hadoop, to tackle the inefficient utilizatio...
Large quantities of data have been generated from multiple sources at exponential rates in the last ...
Compute clusters, consisting of many, uniformly built nodes, are used to run a large spectrum of dif...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datac...
In many clusters and data centers, application frameworks are used that offer programming models suc...
Part 4: Green Computing and Resource ManagementInternational audienceWe present a resource-aware sch...
Today, resource capacity is no longer an issue for running large-scale distributed systems, such as ...
Adaptive workloads can change on–the–fly the configuration of their jobs, in terms of number of proc...
Due to the diversity in the applications that run in large distributed environments, many different ...
The cloud computing paradigm is realized through large scale distributed resource manage-ment and co...
Resource capacity is often over provisioned to primarily deal with short periods of peak load. Shapi...
In order to execute high performance applications on a cluster, it is highly desirable to provide di...
Dynamic resource provisioning, as an important data center software building block, helps to achieve...
As distributed computing systems are used more widely, driven by trends such as 'big data' and cloud...
This research proposes a novel runtime system, Habanero Hadoop, to tackle the inefficient utilizatio...
Large quantities of data have been generated from multiple sources at exponential rates in the last ...
Compute clusters, consisting of many, uniformly built nodes, are used to run a large spectrum of dif...