distributed data-intensive applications
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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High Throughput Data-Compression for Cloud Storage
... As data volumes processed by large-scale distributed data- intensive applications grow at high-speed, an increasing I/O pressure is put on the underlying storage service, which is ...
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Extending Data Facilities using the Framework – HadoopMapReduce M.Sanjay , A.Kumaravel Abstract PDF IJIRMET160208001
... scale data processing by using API's as Message Passing ...larger data volumes since the network bandwidth is the bottleneck and compute nodes becomes ...a distributed parallel computing process for ...
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CHAIO: Enabling HPC Applications on Data-Intensive File Systems
... One data chunk is exclusively used by one process/task in MapReduce ...by data-intensive file ...complex distributed locking mechanism to mitigate the impact of ...a distributed ...
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Management of SOA-based, Data-intensive Applications Deployed in a Distributed Cloud Subject to Response Time Percentile Service Level Agreements.
... enterprise applications has garnered considerable ...SOA-based applications which selects context- providers with an aim to maximize utility based on the accuracy of context-data from the ...
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Scalable Programming and Algorithms for Data Intensive Life Science Applications
... and distributed Cyberinfrastructure to support large scale data ...of applications that test the increasing sophistication of the environment and run on Azure, FutureGrid, or in a workflow linking ...
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MapReduce and Data Intensive Applications
... static/loop-invariant data in memory between iterations; HaLoop extends Hadoop and supports loop-invariant caching and also keeps the reduced outputs in memory in order to provide a faster fix point scheduling; ...
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An extensible and scalable Pilot-MapReduce framework for data intensive applications on distributed cyberinfrastructure
... of data that must be analyzed in scientific applications is increasing ...this data is distributed, thus efficient processing of large distributed datasets is required, whilst ideally ...
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Parallelisation for data intensive applications over peer to peer networks
... aid data intensive ...with distributed computing to easily develop ap- plications in environments that are based on cluster or multi-clusters over differ- ent ...supports data intensive ...
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Energy Consumption in Data Analysis for On-board and Distributed Applications
... of data mining algorithms for mobile and distributed ...specific data mining algorithms from the energy consumption perspec- ...common data analysis techniques on-board computation is a better ...
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On Replication Strategies for Data Intensive Cloud Applications
... a data item can have to realize availability leas required, to decide on where these replicas need to be placed on data nodes taking into account capacity and blocking probability of each ...(Hadoop ...
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A Study on Big Data Technologies
... of data-intensive distributed ...run applications on large number of ...larger data sets. MapReduce is typically used to do distributed computing on clusters of ...huge ...
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Improvement of Data-Intensive Applications Running on Cloud Computing Clusters
... Input data is partitioned and distributed to the computing nodes in the map ...intermediate data generated in this phase are sorted then transferred to the nodes that perform reduce ...intermediate ...
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LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS
... big data storage and its management along with the ...of data thousands of nodes are ...in data corruption due to that the running data- intensive applications unable to read ...
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Distributed Data Mining for Earth and Space Science Applications
... of data from all the sensor nodes followed by data analysis using standard centralized data mining sys- tems would fail to scale ...transmit data over a standard CDPD network from one node to ...
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Research on Real-time Publish/Subscribe System supported by Data-Integration
... number of distributed real-time applications. JMS [3] includes point-to-point and publish/subscribe two information models and provides reliable information transmission, the mechanisms of event and ...
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Bundling Hadoop & Map Reduce for Data-Intensive Computing in Distributed Systems
... and distributed processing, Hadoop offers a complete infrastructure to handle Big ...multiple data source support pose a challenge to Hadoop’s ...Hadoop data management ...
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A Tale of Two Data Intensive Paradigms: Applications, Abstractions and Architectures
... • Before data gets to compute system, there is often an initial data gathering phase which is characterized by a block size and timing. Block size varies from month (Remote Sensing, Seismic) to day ...
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Architectural Issues and Solutions in the Development of Data-Intensive Web Applications
... • Presentation rules can be applied also at runtime, by publishing in the application server the template skeletons and transforming them on the fly, when the HTTP request arrives. This approach is more expensive in ...
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Minimizing technical complexities in emerging cloud computing platforms
... deploying applications on the Cloud as well as blueprints for describing these applications is a compli- cated process because of the need to support tailored applications which may be in addition ...
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