Search Results - (( data application scheduling algorithm ) OR ( code classifications using algorithm ))
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Development of heuristic task scheduling algorithm in cloud computing
Published 2016“…To this direction, in this paper we make a summary of some scheduling algorithms and propose an Enhanced Greedy Heuristic Scheduling Algorithm (EGHSA) for task scheduling adapted for big data applications. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…However, these scheduling algorithms vary in term of their performance and most of these traditional and simple scheduling algorithms may not be efficient for large scale data. …”
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Source code classification using latent semantic indexing with structural and frequency term weighting
Published 2012“…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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Simulated annealing algorithm for scheduling divisible load in large scale data grids.
Published 2009“…This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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Chain coding and pre processing stages of handwritten character image file
Published 2010“…This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. …”
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Improved genetic algorithm for scheduling divisible data grid application
Published 2007“…In this paper, we exploit this property and propose an Improved Genetic Algorithm (IGA) for scheduling divisible data grid applications. …”
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Simulated annealing algorithm for scheduling divisible load in large scale data grids
Published 2008“…This paper proposes a novel simulated annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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MapReduce scheduling algorithms: a review
Published 2020“…Scheduling plays an important role in big data, mainly in reducing the execution time and cost of processing. …”
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MapReduce scheduling algorithms: a review
Published 2018“…Scheduling plays an important role in big data, mainly in reducing the execution time and cost of processing. …”
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A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network
Published 2015“…The novel algorithm has proven to be an effective scheduling technique for smart grid applications.…”
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Survey on job scheduling mechanisms in grid environment
Published 2015“…Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.…”
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