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A systematic review on machine learning and deep learning models for electronic information security in mobile networks
Today's advancements in wireless communication technologies have resulted in a
tremendous volume of data being generated. Most of our information is part of a widespread …
tremendous volume of data being generated. Most of our information is part of a widespread …
Prediction-based scheduling techniques for cloud data center's workload: a systematic review
A cloud data center provides various facilities such as storage, data accessibility, and
running many specific applications on cloud resources. The unpredictable demand for …
running many specific applications on cloud resources. The unpredictable demand for …
DRLBTSA: Deep reinforcement learning based task-scheduling algorithm in cloud computing
Task scheduling in cloud paradigm brought attention of all researchers as it is a challenging
issue due to uncertainty, heterogeneity, and dynamic nature as they are varied in size …
issue due to uncertainty, heterogeneity, and dynamic nature as they are varied in size …
Multi objective prioritized workflow scheduling using deep reinforcement based learning in cloud computing
Workflow Scheduling is a huge challenge in cloud paradigm as many number of workflows
dynamically generated from various heterogeneous resources and task dependencies in …
dynamically generated from various heterogeneous resources and task dependencies in …
Resource allocation with efficient task scheduling in cloud computing using hierarchical auto-associative polynomial convolutional neural network
S Gurusamy, R Selvaraj - Expert Systems with Applications, 2024 - Elsevier
Nowadays, cloud organizations face challenges in managing huge count of data with
various resources due to the prompt expansion of cloud computing (CC) environments with …
various resources due to the prompt expansion of cloud computing (CC) environments with …
An intelligent and interpretable rule-based metaheuristic approach to task scheduling in cloud systems
Metaheuristic algorithms can be very successful in solving scheduling problems. However,
these methods can be slow for time-critical applications due to the iterative stochastic …
these methods can be slow for time-critical applications due to the iterative stochastic …
An efficient and secure model using adaptive optimal deep learning for task scheduling in cloud computing
Recently, cloud computing resources have become one of the trending technologies that
permit the user to manage diverse resources and a huge amount of data in the cloud. Task …
permit the user to manage diverse resources and a huge amount of data in the cloud. Task …
Emerging vm threat prediction and dynamic workload estimation for secure resource management in industrial clouds
The inefficient sharing of industrial cloud resour-ces among multiple users and
vulnerabilities of virtual machines (VM) s and servers prompt unauthorized access to users' …
vulnerabilities of virtual machines (VM) s and servers prompt unauthorized access to users' …
Multi-objective Prioritized Task Scheduler using improved Asynchronous advantage actor critic (a3c) algorithm in multi cloud environment
Task scheduling is a crucial challenge in cloud computing paradigm as variety of tasks with
different runtime processing capacities generated from various heterogeneous devices are …
different runtime processing capacities generated from various heterogeneous devices are …
Imitation learning enabled fast and adaptive task scheduling in cloud
Studies of resource provision in cloud computing have drawn extensive attention, since
effective task scheduling solutions promise an energy-efficient way of utilizing resources …
effective task scheduling solutions promise an energy-efficient way of utilizing resources …