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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Thesis -
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Data discovery algorithm for scientific data grid environment
Published 2005“…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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Article -
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Fuzzy modeling using Bat Algorithm optimization for classification
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Undergraduates Project Papers -
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…This thesis proposes data-intensive workflow optimization algorithms. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). …”
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Algorithmic approaches in model selection of the air passengers flows data
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An Integer Linear Programming model and Adaptive Genetic Algorithm approach to minimize energy consumption of Cloud computing data centers
Published 2018“…This paper focuses on the development of a dynamic task scheduling algorithm by proposing an Integer Linear Programming (ILP) model that minimizes the energy consumption in a Cloud data center. …”
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Impatient job scheduling under cloud computing
Published 2012“…A mathematical model has also been drawn for this problem. It models the cloud computing infrastructure with the ability to inter-operate among the clouds. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Autonomous and deterministic supervised fuzzy clustering
Published 2010“…Besides that, the fast global k-means algorithm 1 also improved the computation time without degrading much the model performance.…”
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Article -
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ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository
Published 2017“…Most of the algorithm and data structure facing a computational problem when they are required to deal with a highly sparse and dense dataset. …”
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Book Chapter -
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Conference or Workshop Item -
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…The major enabler for underlying many big data platforms is certainly the MapReduce computational paradigm. …”
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Academic leadership bio-inspired classification model using negative selection algorithm
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
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Conference or Workshop Item
