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A guide to creating an effective big data management framework
Many agencies and organizations, such as the U.S. Geological Survey, handle massive geospatial datasets and their auxiliary data and are thus faced...
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Leveraging an open source serverless framework for high energy physics computing
CERN (Centre Europeen pour la Recherce Nucleaire) is the largest research centre for high energy physics (HEP). It offers unique computational...
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TMaR: a two-stage MapReduce scheduler for heterogeneous environments
In the context of MapReduce task scheduling, many algorithms mainly focus on the scheduling of Reduce tasks with the assumption that scheduling of...
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A learning-based framework for spatial join processing: estimation, optimization and tuning
The importance and complexity of spatial join operation resulted in the availability of many join algorithms, some of which are tailored for big-data...
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Comprehensive techniques for multi-tenant deep learning framework on a Hadoop YARN cluster
We have designed and implemented a new data processing framework called “MeLoN” (Multi-tenant dEep Learning framework On yarN) which aims to...
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Estimating runtime of a job in Hadoop MapReduce
Hadoop MapReduce is a framework to process vast amounts of data in the cluster of machines in a reliable and fault-tolerant manner. Since being aware...
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A distributed WND-LSTM model on MapReduce for short-term traffic flow prediction
Building data-driven intelligent transportation is a significant task for establishing data-centric smart cities, and exceptionally efficient and...
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Economic mining of thermal power plant based on improved Hadoop-based framework and Spark-based algorithms
In order to explore potential value of explosively growing data in thermal power unit, this paper proposes a big data mining method based on...
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Mining Skyline Patterns from Big Data Environments based on a Spark Framework
Simultaneously, the application of resilient distributed datasets (RDD) in cloud computing provides a good environment for data analysis of big data....
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Efficient allocation of independent gridlet on small, medium, and large grid
Gridlet allocation in a computational grid environment is a major research issue to obtain not only the efficient gridlet allocation technique but...
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Efficient verification of parallel matrix multiplication in public cloud: the MapReduce case
With the advent of cloud-based parallel processing techniques, services such as MapReduce have been considered by many businesses and researchers for...
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Design of ChaApache framework for securing Hadoop application in big data
Hadoop is one of the biggest software structures for distributing the data to compute and handle big data. Big data is a group of composite and...
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A distributed framework for large-scale semantic trajectory similarity join
The similarity join is a common yet expensive operator for large-scale semantic trajectories analytics. In this paper, we propose
DFST , an efficient...
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Parallel computation of probabilistic skyline queries using MapReduce
In recent years, numerous applications have been continuously generating large amounts of uncertain data. The advanced analysis queries such as...
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Distributed probabilistic top-k dominating queries over uncertain databases
In many real-world applications such as business planning and sensor data monitoring, one important, yet challenging, task is to rank objects (e.g.,...
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A new Apache Spark-based framework for big data streaming forecasting in IoT networks
Analyzing time-dependent data acquired in a continuous flow is a major challenge for various fields, such as big data and machine learning. Being...
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Prefetched wald adaptive boost classification based Czekanowski similarity MapReduce for user query processing with bigdata
With large volumes of data being generated in recent years and the inception of big data analytics on social media necessitates accurate user query...
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Mining frequent Itemsets from transaction databases using hybrid switching framework
With the growing volume of data, mining Frequent Itemsets remains of paramount importance. These have applications in various domains such as market...
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Adaptive Weighted Support Vector Machine classification method for privacy preserving in cloud over big data using hadoop framework
Data security is one of the most critical parts of big data investigation. The cloud system applications deal with sensitive information, such as...
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Recognizing MapReduce Straggler Tasks in Big Data Infrastructures Using Artificial Neural Networks
MapReduce framework is used for the distribution and parallelization of large-scale data processing. This framework breaks a job into several...