Search Results - (( problem grid scheduling algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    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
  2. 2

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    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
  3. 3

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    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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    Monograph
  4. 4

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…Experimental evaluation confirmed that the proposed grid scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.…”
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  5. 5

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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    Monograph
  6. 6

    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. …”
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    Article
  7. 7

    Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

    Published 2015
    “…The complexity of scheduling problem is considered as a nondeterministic polynomial complete (NP-complete) problem and therefore, an intelligent algorithm is required to achieve better scheduling solution. …”
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  8. 8

    Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm by Lorpunmanee, Siriluck, Sap, M.N.M, Abdullah, Abdul Hanan, Srinoy, Surat

    Published 2006
    “…The minimization is proposed by using a multiple objective genetic algorithm (GA), because the job scheduling problem is NP-hard problem. …”
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    Article
  9. 9
  10. 10

    Great Deluge and Extended Great Deluge based job scheduling in grid computing using GridSim by Seifaddini, Omid, Abdullah, Azizol, Muhammed, Abdullah, Hussin, Masnida

    Published 2016
    “…Many heuristic algorithms have been proposed for Grid scheduling to avail Grid computing. …”
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    Book Section
  11. 11

    Scheduling jobs in computational grid using hybrid ACS and GA approach by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems.However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time.This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to solve the job scheduling problem.The high level hybridization algorithm will keep the identity of each algorithm in performing the scheduling task.The study focuses on static grid computing environment and the metrics for optimization are the makespan and flowtime.Experiment results show that the proposed algorithm outperforms other stand-alone algorithms such as ant system, genetic algorithms, and ant colony system for makespan.However, for flowtime, ant system and genetic algorithm perform better.…”
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    Conference or Workshop Item
  12. 12

    Highest response ratio next (HRRN) vs first come first served (FCFS) scheduling algorithm in grid environment by Latip, Rohaya, Idris, Zulkhairi

    Published 2011
    “…Research on Grid scheduling nowadays, focuses in solving three problems such as finding a good algorithm, automating the process, and building a flexible, scalable, and efficient scheduling mechanism. …”
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  13. 13

    Bee foraging behaviour techniques for grid scheduling problem by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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    Article
  14. 14

    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

    Published 2007
    “…However, the major problems include optimal job scheduling, and which grid nodes allocate the resources for each job. …”
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    Article
  15. 15

    COMPARATIVE PERFORMANCE OF SOME HYBRID HEURISTICS SCHEDULING ALGORITHMS BASED ON SLTR AND DEADLINE FOR COMPUTATIONAL GRID by AHMED ABBA, HARUNA

    Published 2013
    “…Grid scheduling is an essential element of a Computational Grid infrastructure. …”
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    Thesis
  16. 16

    A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. by Ambursa, Faruku Umar, Latip, Rohaya

    Published 2013
    “…Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Several researches have been conducted to tackle the problems of task scheduling for the heterogeneous and dynamic grid systems using different bio-inspired mechanisms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO). …”
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    Article
  17. 17

    Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
    “…Metaheuristic algorithms have been used to solve scheduling problems in grid computing.However, stand-alone metaheuristic algorithms do not always show good performance in every problem instance. …”
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    Article
  18. 18

    New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

    Published 2012
    “…Job scheduling is one of the main factors affecting grid computing performance. …”
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    Conference or Workshop Item
  19. 19

    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
    “…This paper concentrates on the design and implement of the grid system for study of adaptive job scheduling algorithm based on GridSim. …”
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    Article
  20. 20

    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

    Published 2018
    “…Grid system has been used to solve complex problems that need years to be executed. …”
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    Thesis