Search Results - (( java simulation optimization algorithm ) OR ( _ utilization model algorithm ))
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1
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…Global pheromone update is performed after the completion of 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. …”
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Monograph -
2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of 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 existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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3
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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4
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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5
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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7
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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8
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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9
SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Enhanced utility accrual scheduling algorithms for adaptive real time system.
Published 2009“…Problem statement: This study proposed two utility accrual real time scheduling algorithms named as Preemptive Utility Accrual Scheduling (PUAS) and Non-preemptive Utility Accrual Scheduling (NUAS) algorithms. …”
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11
A Non-preemptive Utility Accrual Scheduling Algorithm in iAdaptive Real Time System
Published 2008“…In this paper, we proposed a Non-preemptive Utility Accrual Scheduling (or NUAS) algorithm that enhanced the existing General Utility Scheduling (or GUS) proposed by Peng Li [1]. …”
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Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization
Published 2023“…The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). …”
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13
Utilization of canny and velocity bunching algorithms for modelling shoreline change
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14
Improving utility accrual scheduling algorithm for adaptive real-time system
Published 2008“…The proposed algorithm focused on an independent task model, which works on deadline constraints that are specified by using step time/utility functions (or TUFs). …”
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Conference or Workshop Item -
15
A preemptive utility accrual scheduling algorithm in adaptive real time system.
Published 2008“…In this paper, we propose a preemptive utility accrual scheduling(or PUAS) algorithm as an enhancement to General Utility Scheduling ( or GUS) algorithm proposed by Peng Li [1]. …”
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16
Fault recovery mechanisms in utility accrual real time scheduling algorithm
Published 2009“…In this paper, we proposed two recovery solutions over the existing error-free utility accrual scheduling algorithm known as General Utility Accrual Scheduling algorithm (or GUS) (Peng Li, 2004). …”
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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing
Published 2019“…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. SecPath is evaluated with several variations using 400 nodes in WSN deployments as well as large-scale simulations. …”
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18
A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System
Published 2020“…The collected of real vibration data through experimental study was then utilized to develop the dynamic system model based on linear autoregressive with exogenous (ARX) model structure and optimized by flower pollination algorithm (FPA). …”
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Proceeding -
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…To consistently estimate relevant thresholds from the threshold set obtained by the group LASSO, the backward elimination algorithm (BEA) is utilized. We extend BCD algorithm for the multivariate SETAR model, our second model. …”
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UMK Etheses -
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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