Data intensive applications
Fine Grained Interference and Deadline Aware Scheduling For Data Intensive Applications in Virtualized Environments
... to data-intensive ...the data-intensive applications that consume a significant amount of I/O bandwidth and CPU cycles, we choose to characterize each application by four key parameters ...
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Matching Data Intensive Applications and Hardware/Software Architectures
... big data applications to identify characteristics of data intensive applications and propose a big data version of the famous Berkeley dwarfs and NAS parallel ...
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Significance of Hierarchical and Markov Clustering in Grouping Aware Data Placement for Data Intensive Applications Having Interest Locality
... large-scale data management to achieve improved performance in terms of reduced execution time, through ODP, especially when data-intensive applications exhibit interest ...
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Location-aware Associated Data Placement for Geo-distributed Data-intensive Applications
... Abstract—Data-intensive applications need to address the problem of how to properly place the set of data items to distributed storage ...multiple data items in one transaction, ...
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Review On Data Replication with QoS and Energy Consumption for Data Intensive Applications in Cloud Computing
... for applications, data and file ...cloud applications management ,cloud backup and data recovery, cloud interoperability & data analytics, liability issues for data loss on ...
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Using Pre-Execution and Helper Threads for Speeding Up Data Intensive Applications
... modern data intensive applications memory latency is a real concern ...to data accessed in the ...the data is requested it will be served by the cache saving the CPU from severe ...
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LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS
... many data intensive cloud ...is data replication that brings data nearer to data intensive ...high data availability. In this paper we study data replication ...
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Improvement of Data-Intensive Applications Running on Cloud Computing Clusters
... for data-intensive computing, therefore, HDFS RPP has become popular research area to improve the data partitioning and place- ...each data file is partitioned and stored as a sequence of ...
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MapReduce and Data Intensive Applications
... • MapReduce is a programming model and implementation for processing and generating large data sets – Focus developer time/effort on salient unique, distinguished application requirement[r] ...
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Data Intensive Applications on Clouds
... DPFS Data Parallel File System: Support of file systems like Google (MapReduce), HDFS (Hadoop) or Cosmos (dryad) with compute-data affinity optimized for data processing Table: Support of Table ...
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Parallelisation for data intensive applications over peer to peer networks
... 72 range results are plotted in Fig. 4-4 and 4-5 respectively. The number of DHT in- sertions is reduced by one if N increases by one, which is apparent in Fig. 4-4. In Fig. 4-5, it is not easy to see the plots where N = ...
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An extensible and scalable Pilot-MapReduce framework for data intensive applications on distributed cyberinfrastructure
... distributed infrastructures effectively made the design and development of distributed applications more complex task [23]. For example, many programming systems and tools for distributed appli- cations are either ...
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Tools Supporting Generation of Data-Intensive Applications for a Web Environment 1, 2
... Integration of a database query language with an object-oriented programming lan- guage is based on introduction into the language syntax level a syntactic sugar in a form of keywords like select-from-where together with ...
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Data-Intensive Applications on HPC Using Hadoop, Spark and RADICAL-Cybertools
... ● Application-level scheduling enables the implementation of a data- aware resource manager for analytics applications.. ● Interoperability Layer between Hadoop (Apache Big Data Stack ([r] ...
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Hybrid Cloud and Cluster Computing Paradigms for Scalable Data Intensive Applications
... Need is pervasive – Large and high dimensional data are everywhere: biology, physics, Internet, … – Visualization can help data analysis Visualization of large datasets with high perform[r] ...
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Enhancing Data Processing And Management For Big-Data Intensive Applications Based On Cloud Computing
... Big data analytics is the process of analyzing a huge amount of data or large volume data sets to interpret useful information and also detect the hidden patterns that help the organization in making ...
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Geoinformatics and Data Intensive Applications on Clouds
... • Broad Overview: Trends from Data Deluge to Clouds • Clouds, Grids and Supercomputers: Infrastructure and Applications that work on clouds • MapReduce and Iterative MapReduce for non tr[r] ...
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Database Sampling to Support the Development of Data Intensive Applications
... other data sources to populate the constructing prototype ...of data, which makes them particu- larly appropriate for performance evaluation of information ...operational data and the inclusion of ...
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Multicore and Cloud Technologies for Data Intensive Applications
... We show how clusters of Multicore systems give high parallel performance while Cloud technologies Hadoop from Yahoo and Dryad from Microsoft allow the integration of the large data repos[r] ...
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Sensors and other Data Intensive Applications on Clouds
... DPFS Data Parallel File System: Support of file systems like Google (MapReduce), HDFS (Hadoop) or Cosmos (dryad) with compute-data affinity optimized for data processing Table: Support of Table ...
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