Search Results - (( java optimization based algorithm ) OR ( data application scheduling algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Article -
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Smart student timetable planner
Published 2025“…A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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Final Year Project / Dissertation / Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
Published 2013“…The optimization of a computationally intensive algorithm such as this on a mobile platform is challenging due to the limited resources available. …”
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Conference or Workshop Item -
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Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…Hence, the objective of this research is to propose suitable and optimize algorithm for ANPR system on Android mobile phone. …”
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Book -
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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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Proceeding Paper -
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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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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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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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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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Conference or Workshop Item -
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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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Conference or Workshop Item -
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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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Enhanced utility accrual scheduling algorithms for adaptive real time system.
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Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds
Published 2018“…Finally, we expected the scheduling algorithms PDC and DCCP to be improve the Cloud resource usage high efficiency in the IaaS Cloud with efficient scheduling for scientific workflow.…”
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Thesis -
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). The study compares the performance of WOA with various existing strategies, such as Greedy, Density, TVG, Union, ParaOrder, ReqOrder, ITTDG, AURA, Java Algorithm (CTJ), TTSGA, and AFA. …”
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