[HTML][HTML] A systematic review of energy management strategies for resource allocation in the cloud: Clustering, optimization and machine learning

S Jayaprakash, MD Nagarajan, RP Prado… - Energies, 2021‏ - mdpi.com
Nowadays, many organizations and individual users are employing cloud services
extensively due to their efficiency, reliability and low cost. A key aspect for cloud data centers …

Adaptive computational solutions to energy efficiency in cloud computing environment using VM consolidation

B Magotra, D Malhotra, AK Dogra - Archives of computational methods in …, 2023‏ - Springer
Cloud Computing has emerged as a computing paradigm where services are provided
through the internet in recent years. Offering on-demand services has transformed the IT …

Energy-latency tradeoff for dynamic computation offloading in vehicular fog computing

R Yadav, W Zhang, O Kaiwartya… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Vehicular Fog Computing (VFC) provides solutions to relieves overload cloudlet nodes,
reduces service latency during peak times, and saves energy for battery-powered cloudlet …

Smart healthcare: RL-based task offloading scheme for edge-enable sensor networks

R Yadav, W Zhang, IA Elgendy, G Dong… - IEEE Sensors …, 2021‏ - ieeexplore.ieee.org
With the wide application of Internet-of-Medical-Things (IoMTs) or sensor nodes which
equipped with sensors. These networked sensors are used to gather enormous data from …

PAPSO: A power-aware VM placement technique based on particle swarm optimization

A Ibrahim, M Noshy, HA Ali, M Badawy - IEEE Access, 2020‏ - ieeexplore.ieee.org
With the widespread usage of cloud computing to benefit from its services, cloud service
providers have invested in constructing large scale data centers. Consequently, a …

Kubernetes-oriented microservice placement with dynamic resource allocation

Z Ding, S Wang, C Jiang - IEEE Transactions on Cloud …, 2022‏ - ieeexplore.ieee.org
Microservices and Kubernetes are widely used in the development and operations of cloud-
native applications. By providing automated placement and scaling, Kubernetes has …

Adaptive client selection in resource constrained federated learning systems: A deep reinforcement learning approach

H Zhang, Z **e, R Zarei, T Wu, K Chen - IEEE Access, 2021‏ - ieeexplore.ieee.org
With data increasingly collected by end devices and the number of devices is growing
rapidly in which data source mainly located outside the cloud today. To guarantee data …

DCHG-TS: a deadline-constrained and cost-effective hybrid genetic algorithm for scientific workflow scheduling in cloud computing

A Iranmanesh, HR Naji - Cluster Computing, 2021‏ - Springer
Cloud infrastructures are suitable environments for processing large scientific workflows.
Nowadays, new challenges are emerging in the field of optimizing workflows such that it can …

Migration-based load balance of virtual machine servers in cloud computing by load prediction using genetic-based methods

LH Hung, CH Wu, CH Tsai, HC Huang - IEEE Access, 2021‏ - ieeexplore.ieee.org
This paper presents a two-stage genetic mechanism for the migration-based load balance of
virtual machine hosts (VMHs) in cloud computing. Previous methods usually assume this …

Two-phase industrial manufacturing service management for energy efficiency of data centers

W Zhang, R Yadav, YC Tian, SKS Tyagi… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
Data-driven industrial manufacturing services are proliferating. They use large amounts of
data generated from Industrial-Internet-of-Things (IIoT) devices for intelligent services to end …