Search Results - (( using combination cloud algorithm ) OR ( simulation optimization method algorithm ))

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  1. 1

    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES) by Kamal Khairi Supaprhman

    Published 2022
    “…The natural evolution optimization algorithm which is genetic algorithm can be improve by combining the nature meta-heuristic algorithms which is bald eagle search to improve the makespan of genetic algorithm using cloudsim that need to be implement on the eclipse platform. …”
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    Academic Exercise
  2. 2

    Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed, DR Janardhana, DR Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

    Published 2024
    “…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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    Conference or Workshop Item
  3. 3

    Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed I, D R, Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

    Published 2024
    “…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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    Conference or Workshop Item
  4. 4

    Tag clouds algorithm with the inclusion of personality traits by Ahmad Affandi, Supli

    Published 2015
    “…The main contribution of this research is the tag cloud layout styles algorithm, which combines the concept of personality traits and characteristics of colors and shapes. …”
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    Thesis
  5. 5

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…In this project, Genetic Algorithms (GA) is combine Moth Flame Optimization (MFO) to improve the cloud computing environment. …”
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    Academic Exercise
  6. 6

    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…Then they are assigned to the machines according to the assignment algorithm for job combinations, which is a special integer partition algorithm. …”
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    Thesis
  7. 7

    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Article
  8. 8

    Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing by Naha, Ranesh Kumar

    Published 2015
    “…Proposed cloud brokering algorithms works with different types of cloud provider and deal with various user requirements. …”
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    Thesis
  9. 9

    Improving energy consumption in cloud computing datacenters using a combination of energy-aware resource allocation and scheduling mechanism by Khalil Abd., Sura

    Published 2017
    “…In this study, to improve the utilization of cloud resources and reduce the energy consumption of datacenters, a combination of energy-aware resource allocation and scheduling mechanism including DNA based Fuzzy Genetic Algorithm (DFGA) is proposed. …”
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    Thesis
  10. 10

    Genetic algorithm optimized network in cloud data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2016
    “…This could be considered a combinatorial problem, which in our methodology is attempted to be solved using genetic algorithm. The generated network card configurations adapt to the typical characteristics of cloud network traffic pattern. …”
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    Article
  11. 11

    Privacy-preserving multi-keyword hybrid search over encrypted data in cloud by Singh, N., Kumar, J., Singh, A.K., Mohan, A.

    Published 2022
    “…This algorithmic combination is able to predict the privacy ranking measure of the retrieved data. …”
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    Article
  12. 12

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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    Undergraduates Project Papers
  13. 13

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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    Thesis
  14. 14

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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    Thesis
  15. 15

    Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

    Published 2025
    “…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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    Thesis
  16. 16

    Privacy-preserving multi-keyword hybrid search over encrypted data in cloud by Singh, N., Kumar, J., Singh, A.K., Mohan, A.

    Published 2022
    “…This algorithmic combination is able to predict the privacy ranking measure of the retrieved data. …”
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    Article
  17. 17

    Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2019
    “…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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    Proceeding Paper
  18. 18

    Asynchronous simulated kalman filter optimization algorithm by Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd Aziz, Tasiransurini, Ab Rahman

    Published 2018
    “…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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    Article
  19. 19

    Alignment of 3D laser scanner point clouds using photogrammetric targets by Majid, Zulkepli, Setan, Halim, Chong, Albert K.

    Published 2006
    “…For complete 3D model generation, the scanning images is needed to be registered (combined) and merged together. Existing registration method used corresponding features between the two scanned images as registration primitive and finally 3D transformation algorithm was applied to combine the images. …”
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    Conference or Workshop Item
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