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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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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique
Published 2008“…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
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Rule pruning techniques in the ant-miner classification algorithm and its variants: A review
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QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)
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Ant colony optimization algorithm for rule based classification: Issues and potential
Published 2018“…Nevertheless, ACO also has several drawbacks that may reduce the classification accuracy and the computational time of the algorithm. This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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Heuristic factors in ant system algorithm for course timetabling problem
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Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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Big data clustering using grid computing and ant-based algorithm
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Enhanced ant colony optimization for grid load balancing
Published 2011“…This paper proposes an Enhanced Ant Colony Optimization (EACO) algorithm for dynamic schedulling and load balancing in a grid computer system. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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Load balancing using enhanced ant algorithm in grid computing
Published 2010“…Load balancing is one of the critical issues that must he considered in managing a grid computing environment.It is complicated due to the distributed and heterogeneous nature of the resources.An enhanced ant algorithm for load balancing in grid computing is proposed in this papcr.The proposed algorithm will determine the best resource to he allocated to the jobs based on job characteristics and resource capacity, and at the same time to balance the entire resources.The proposed algorithm focuses on local pheromone trail update and trail limit. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism
Published 2008“…Computational tests show promises of the new algorithm.…”
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Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid
Published 2015“…This study proposes a high level hybrid approach between ant colony system and genetic algorithm for job scheduling in grid computing.The proposed approach is based on a high level hybridization.The proposed hybrid approach is evaluated using the static benchmark problems known as ETC matrix.Experimental results show that the proposed hybridization between the two algorithms outperforms the stand-alone algorithms in terms of best and average makespan values.…”
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Grid load balancing using enhance ant colony optimization
Published 2011“…This study presents a new algorithm based on ant colony optimization for load balancing management in grid computing. …”
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Ant system-based feature set partitioning algorithm for K-NN and LDA ensembles construction
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