A systematic review on machine learning and deep learning models for electronic information security in mobile networks

C Gupta, I Johri, K Srinivasan, YC Hu, SM Qaisar… - Sensors, 2022 - mdpi.com
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 …

Prediction-based scheduling techniques for cloud data center's workload: a systematic review

S Kashyap, A Singh - Cluster Computing, 2023 - Springer
A cloud data center provides various facilities such as storage, data accessibility, and
running many specific applications on cloud resources. The unpredictable demand for …

DRLBTSA: Deep reinforcement learning based task-scheduling algorithm in cloud computing

S Mangalampalli, GR Karri, M Kumar, OI Khalaf… - Multimedia tools and …, 2024 - Springer
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 …

Multi objective prioritized workflow scheduling using deep reinforcement based learning in cloud computing

S Mangalampalli, SS Hashmi, A Gupta, GR Karri… - IEEE …, 2024 - ieeexplore.ieee.org
Workflow Scheduling is a huge challenge in cloud paradigm as many number of workflows
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 …

An intelligent and interpretable rule-based metaheuristic approach to task scheduling in cloud systems

C Barut, G Yildirim, Y Tatar - Knowledge-Based Systems, 2024 - Elsevier
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 …

An efficient and secure model using adaptive optimal deep learning for task scheduling in cloud computing

S Badri, DM Alghazzawi, SH Hasan, F Alfayez… - Electronics, 2023 - mdpi.com
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 …

Emerging vm threat prediction and dynamic workload estimation for secure resource management in industrial clouds

D Saxena, R Gupta, AK Singh… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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' …

Multi-objective Prioritized Task Scheduler using improved Asynchronous advantage actor critic (a3c) algorithm in multi cloud environment

SS Mangalampalli, GR Karri, SN Mohanty, S Ali… - IEEE …, 2024 - ieeexplore.ieee.org
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 …

Imitation learning enabled fast and adaptive task scheduling in cloud

KX Kang, D Ding, HM **e, LH Zhao, YN Li… - Future Generation …, 2024 - Elsevier
Studies of resource provision in cloud computing have drawn extensive attention, since
effective task scheduling solutions promise an energy-efficient way of utilizing resources …