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  1. 1
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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    Thesis
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  2. 2
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
    “…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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    Final Year Project / Dissertation / Thesis
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  3. 3
    HATS: HetTask scheduling

    HATS: HetTask scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

    Published 2022
    “…The proposed algorithm adopts an updated multi-level hyper-graph partitioning approach. …”
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  4. 4
    Benchmark simulator with dynamic environment for job scheduling in grid computing

    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Job scheduling algorithm has a significant influence on grid computing performance. …”
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    Conference or Workshop Item
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  5. 5
    Analysis and modeling of database storage optimization power consumption usage for green data centers

    Analysis and modeling of database storage optimization power consumption usage for green data centers by Wan Noor Hamiza, Wan Ali

    Published 2014
    “…The proxies can be discovered by using a developed algorithm of functional dependencies (FDs) called as TANE algorithm. …”
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  6. 6
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    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
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  7. 7
    Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism

    Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism by Alomari M.F., Mahmoud M.A., Gharaei N., Rasool S.M., Hasan R.A.

    Published 2025
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    Conference paper
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  8. 8
    A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments

    A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments by Haque, Najmul, Zafril Rizal, M. Azmi, Murad, Saydul Akbar

    Published 2026
    “…An essential element of cloud computing is effective job scheduling, which optimizes resource utilization and minimizes operational costs. …”
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  9. 9
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
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  10. 10
    OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network

    OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen, Latip, Rohaya

    Published 2019
    “…This study presents an optimal tasks scheduling algorithm by enhancing Max-Min algorithm. …”
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  11. 11
    Modeling approach of cloud 4D printing service composition optimization based on non-dominated sorting genetic algorithm III

    Modeling approach of cloud 4D printing service composition optimization based on non-dominated sorting genetic algorithm III by Liu, Jiajia, Zainudin, Edi Syams, As'arry, Azizan, Ismail, Mohd Idris Shah

    Published 2024
    “…We propose a comprehensive multiobjective optimization model for cloud-based 4D printing service portfolios, incorporating the intricate complexities of 4D printing services and assessing the efficacy of the Non-Dominated Sorting Genetic Algorithm III (NSGA III) in optimizing these service portfolios to meet dynamic demands. …”
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  12. 12
    Genetic algorithm optimized network in cloud data centre

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

    Published 2016
    “…However, network device optimization in a cloud network has never been done according to our review. …”
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  13. 13
    Resource scheduling algorithm with load balancing for cloud service provisioning

    Resource scheduling algorithm with load balancing for cloud service provisioning by Priya, V., Sathiya Kumar, C., Kannan, R.

    Published 2019
    “…These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. …”
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  14. 14
    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing

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

    Published 2013
    “…In this study, load balancing technique in Cloud Computing called Quantum Particle Swarm Optimization (QPSO) technique proposed by considering only minimization of makespan, computation cost and communication cost. …”
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  15. 15
    Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment

    Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment by Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Al-Khasawneh, Ahmad

    Published 2018
    “…In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. …”
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  16. 16
    Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment

    Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment by Mohammed, Faten Ameen Saif

    Published 2019
    “…Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. …”
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  17. 17
    An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud

    An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud by Sa’ad, Suleiman, Muhammed, Abdullah, Abdullahi, Mohammed, Abdullah, Azizol, Ayob, Fahrul Hakim

    Published 2021
    “…Therefore, in this paper, we propose a metaheuristic enhanced discrete symbiotic organism search (eDSOS) algorithm for optimal task scheduling in the cloud computing setting. …”
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  18. 18
    Optimized load balancing for efficient resource provisioning in the cloud

    Optimized load balancing for efficient resource provisioning in the cloud by Naha, Ranesh Kumar, Othman, Mohamed

    Published 2014
    “…In this paper, we propose an algorithm entitled Optimized Load Balancing (OLB), which aims to carry out efficient load balancing by improving processing and response time. …”
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  19. 19
    Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing

    Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

    Published 2023
    “…Second, proposed a Multi-objective Grey Wolf Optimizer (MGWO) algorithm for optimizing task scheduling to reduce transmission delay on edge-cloud computing and energy consumption on edge-fog computing. …”
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  20. 20
    Individual-tree segmentation and extraction based on LiDAR point cloud data

    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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