data-intensive distributed applications
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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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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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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Management of SOA-based, Data-intensive Applications Deployed in a Distributed Cloud Subject to Response Time Percentile Service Level Agreements.
... In this chapter we analyze percentile Service Level Agreements. From the cloud consumer’s point of view, percentiles of response times, as opposed to averages, provide a better control of variability in delays ...
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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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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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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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Scalable Programming and Algorithms for Data Intensive Life Science Applications
... and data mining algorithms need only this MPI subset, and we have used this in our initial choice of evaluating ...a distributed workflow) on ...map applications using the broadcast/reduce subset of ...
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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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Location-aware Associated Data Placement for Geo-distributed Data-intensive Applications
... requested data closer to the users is the moti- vation of most existing work on data placement, which helps to reduce the latency experienced by the users and lower the relaying traffic among ...network ...
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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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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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Distributed Data Mining for Earth and Space Science Applications
... pervasive distributed computing environments in many ...of distributed massive data repositories such as NASA Earth Science Distributed Data Archives and virtual observatories are some ...
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Research on Real-time Publish/Subscribe System supported by Data-Integration
... fully distributed network structure of data exchange, in which each node mainly includes two parts, InfoRepo and database management system (DBMS) in ...make data can be shared in the whole ...
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LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS
... the applications with high QoS should be replicated ...a data access time than the normal ...perform data replication. We have to sort all the applications according to their QoS requirement ...
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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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