[PDF] Top 20 Clouds and MapReduce for Scientific Applications
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Clouds and MapReduce for Scientific Applications
... and MapReduce for Scientific Applications Introduction Cloud computing[1] is at the peak of the Gartner technology hype curve[2] but there are good reasons to believe that as it matures that it will ... See full document
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Cost efficient scheduling of MapReduce applications on public clouds
... Public Clouds have become a natural host for these MapReduce ...greedy-based MapReduce application scheduling algorithm (MASA) that considers the user’s constraints in order to minimize cost of ... See full document
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Optimizing data storage for MapReduce applications in the Azure Clouds
... execute MapReduce jobs, called Dryad [23]. Dryad is superior to MapReduce from the point of view of the workflows that can be ...in clouds. Hence, at this point there is nothing provided for the ... See full document
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MapReduce in the Clouds for Science
... clusters. MapReduce distributed data processing architecture has become the weapon of choice for data-intensive analyses in the clouds and in commodity clusters due to its excellent fault tolerance ... See full document
8
A Performance Evaluation of Azure and Nimbus Clouds for Scientific Applications
... using clouds for scientific ...public clouds, focusing on tightly coupled, MPI-style ...private clouds in order to assess the performance trade-offs, scala- bility issues and the main limiting ... See full document
7
Hadoop MapReduce for Mobile Clouds
... computing applications without direct knowledge of underlying distributed systems ...these applications have severe energy and reliability constraints ...mobile clouds. We have developed the Hadoop ... See full document
15
Dependable mapreduce in a cloud-of-clouds
... out MapReduce to multiple clouds and, simultaneously, tolerating the new faults introduced by such multi-cloud envi- ...scales MapReduce computations to multiple ...The clouds just need to run ... See full document
170
A Chemistry-Inspired Workflow Management System for Scientific Applications in Clouds
... Services, scientific ap- plications are more and more designed as temporal composition of services, commonly referred to as, ...platforms. Scientific applications started to be deployed over emerging ... See full document
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Resilin: Elastic MapReduce for Private and Community Clouds
... proprietary, MapReduce can be leveraged by anyone using the free and open source Apache Hadoop frame- ...Elastic MapReduce, a web service enabling users to run MapReduce ...Elastic MapReduce ... See full document
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Resilin: Elastic MapReduce over Multiple Clouds
... The MapReduce programming model, introduced by Google, offers a simple and efficient way of performing distributed computation over large data ...proprietary, MapReduce can be leveraged by anyone using the ... See full document
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ANALYSIS OF SECURITY AND PRIVACY FEATURES IN MAPREDUCE ON CLOUDS
... Hadoop. MapReduce is extensively used daily around the world as an efficient distributed computation tool for a huge class of problems such as search, clustering, log analysis, different types of join operations, ... See full document
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Cost-Minimizing Preemptive Scheduling of MapReduce Workloads on Hybrid Clouds
... hybrid clouds, consisting of private infrastructure owned by themselves and public clouds such as Amazon EC2, to process their spiky MapReduce workloads, which fully utilize their own on-premise ... See full document
6
A Virtual Machine Consolidation Framework for MapReduce Enabled Computing Clouds
... computing clouds, it is of the cloud providers’ economic interests to correctly consolidate the work- load of the virtual machines (VMs) into the suitable physical servers in the cloud data center in order to ... See full document
8
Cost-minimizing preemptive scheduling of mapreduce workloads on hybrid clouds
... hybrid clouds, consisting of private infrastructure owned by themselves and public clouds such as Amazon EC2, to process their spiky MapReduce workloads, which fully utilize their own on-premise ... See full document
7
Scalable Parallel Computing on Clouds Using Twister4Azure Iterative MapReduce
... iterative MapReduce runtime for Windows Azure Cloud that has been developed utilizing Azure cloud infrastructure ...easy-to-use MapReduce programming model with iterative extensions, enabling a wide array ... See full document
18
Chrysaor: Fine-Grained, Fault-Tolerant Cloud-of-Clouds MapReduce
... significant penalty for the baseline case (i.e., without faults) in most workloads. In summary, the main contribution of this work is Chrysaor 1 , a system that leverages from several Hadoop MapReduce runtimes ... See full document
10
MapReduce in the Clouds for Science
... Analyze the performance and viability of performing 2 types of bioinformatics computations using MapReduce.. in cloud environments.[r] ... See full document
22
Scaling MapReduce Applications across Hybrid Clouds to Meet Soft Deadlines
... processed. MapReduce is among the most popular models for development of Cloud ...priority applications, we propose a policy for dynamic provisioning of Cloud resources to speed up execution of ... See full document
8
Classification On The Clouds Using MapReduce
... Since sending the instances between jobs is clearly a very costly option, one of the best options seems to be to iterate the entire data set in each job, and for each example tra[r] ... See full document
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MapReduce-based Parallelization of Sparse Matrix Kernels for Large-scale Scientific Applications
... the MapReduce paradigm by introducing new data types and efficient communication routines that are centered around using ...conventional MapReduce program, an MR-MPI program must make at least three ... See full document
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