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  1. 1
    Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

    Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions by Akhlaqi, Mohammad Yahya, Mohd Hanapi, Zurina

    Published 2023
    “…Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. …”
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  2. 2
    On protecting data storage in mobile cloud computing paradigm

    On protecting data storage in mobile cloud computing paradigm by Abdalla , Al-kindy Athman, Pathan, Al-Sakib Khan

    Published 2014
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  3. 3
    A new priority rule cloud scheduling technique that utilizes gaps to increase the efficiency of jobs distribution

    A new priority rule cloud scheduling technique that utilizes gaps to increase the efficiency of jobs distribution by Saydul Akbar, Murad

    Published 2023
    “…These limitations lead to the poor performance of cloud-based mobile applications and other cloud services. …”
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  4. 4
    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment

    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

    Published 2021
    “…The system uses a LiDAR-IMU tight coupling odometry method to reconstruct a point cloud map of the area surveyed. After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. …”
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  5. 5
    Mobile agent based multi-layer security framework for cloud data centers

    Mobile agent based multi-layer security framework for cloud data centers by Uddin, Mueen, Memon, Jamshed, Alsaqour, Raed A., Shah, Asadullah, Abdul Rozan, Mohd Zaidi

    Published 2015
    “…Objective:This paper proposes a new mobile agent based cloud security framework comprising four different security and authentication layers to establish the trust relationship between two entities before using cloud services. …”
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  6. 6
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  7. 7
    A new efficient checkpointing algorithm for distributed mobile computing

    A new efficient checkpointing algorithm for distributed mobile computing by Mansouri, Houssem, Badache, Nadjib, Aliouat, Makhlouf, Pathan, Al-Sakib Khan

    Published 2015
    “…Such instability poses serious challenge for fault tolerant distributed mobile applications. Therefore, the classical checkpointing techniques, which make the applications more failure-resistant, are not always compatible with the mobile context. …”
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  8. 8
    Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing

    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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  9. 9
    A priority based job scheduling algorithm in cloud computing

    A priority based job scheduling algorithm in cloud computing by Shamsollah, Ghanbari, Othman, Mohamed

    Published 2012
    “…Nowadays cloud computing has become a popular platform for scientific applications. …”
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  10. 10
    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
    “…The result of the algorithm performance will be appeared in web application system. …”
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  11. 11
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
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  12. 12
    Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds

    Deadline guarantee for scientific workflow using dynamic scheduling algorithms on IaaS clouds by Alqaisy, Sarah Abdulrahman Shukur

    Published 2018
    “…Finally, we expected the scheduling algorithms PDC and DCCP to be improve the Cloud resource usage high efficiency in the IaaS Cloud with efficient scheduling for scientific workflow.…”
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  13. 13
    Modified workflow scheduling using hybrid PSO-GA algorithm in cloud computing

    Modified workflow scheduling using hybrid PSO-GA algorithm in cloud computing by Oke, Omotayo Patrick

    Published 2019
    “…The goal of the Hybrid GA-PSO algorithm is to reduce the makespan and cost and balance the load of dependent tasks in cloud computing environments over the heterogonous resources. …”
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  14. 14
    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)

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

    Published 2022
    “…Task scheduling and resource allocation are essential aspects of cloud computing. This Study proposes task scheduling in cloud computing using a hybrid genetic algorithm, and bald eagle search proposed to solve the task scheduling problem. …”
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  15. 15
    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance

    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

    Published 2023
    “…The cloud paradigm has arisen due to a rapid growth in applications and data sizes. …”
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  16. 16
    Two objectives big data task scheduling using swarm intelligence in cloud computing

    Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

    Published 2016
    “…Although many scheduling algorithms have been implemented for cloud computing, it has been realized that most of the applications nowadays require different objectives that simple scheduling algorithms fail to achieve. …”
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  17. 17
    New Lightweight Identity Based Encryption Algorithm for Mobile Device: Preliminary Study

    New Lightweight Identity Based Encryption Algorithm for Mobile Device: Preliminary Study by Norhidayah, Muhammad, Jasni, Mohamad Zain, Md Yazid, Mohd Saman

    Published 2012
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  18. 18
    Evaluation of cloud brokering algorithms in cloud based data center

    Evaluation of cloud brokering algorithms in cloud based data center by Naha, Ranesh Kumar, Othman, Mohamed, Akhter, Nasrin

    Published 2015
    “…In this paper, two new cloud brokering algorithms, and their initial evaluation, are proposed.…”
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  19. 19
    Dynamic load balancing algorithm based on deadline constrained in cloud environment

    Dynamic load balancing algorithm based on deadline constrained in cloud environment by Mansur, Muzzammil

    Published 2019
    “…Cloud Service Provider (CRP) provides services on demand to the users, as the application as well as the numbers of users are gradually growing over the cloud environment which leads to the increasing in the workload that are deployed over the virtual machine (VM). …”
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  20. 20
    Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System

    Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System by Nwogbaga, Nweso Emmanuel

    Published 2023
    “…Most times, the approach of relying on cloud infrastructure for IoT application analysis may be inefficient in terms of the limited battery life of the mobile devices, resource allocation algorithm delay, and computational offloading processes that sometimes increases the response time. …”
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