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Auto-scaling techniques in container-based cloud and edge/fog computing: Taxonomy and survey
The long-held dream of computing as a service was realized with the emergence of cloud
computing. Recently, fog and edge computing have been introduced as extensions of cloud …
computing. Recently, fog and edge computing have been introduced as extensions of cloud …
Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanism
The resources required to service cloud computing applications are dynamic and fluctuate
over time in response to variations in the volume of incoming requests. Proactive …
over time in response to variations in the volume of incoming requests. Proactive …
[HTML][HTML] Artificial intelligence for the management of servitization 5.0
Purpose—The sale of physical products has been manufacturing companies' main revenue
source. A trend is known as servitization for earning revenue comes from services. With the …
source. A trend is known as servitization for earning revenue comes from services. With the …
Magicscaler: Uncertainty-aware, predictive autoscaling
Predictive autoscaling is a key enabler for optimizing cloud resource allocation in Alibaba
Cloud's computing platforms, which dynamically adjust the Elastic Compute Service (ECS) …
Cloud's computing platforms, which dynamically adjust the Elastic Compute Service (ECS) …
A survey on scheduling techniques in computing and network convergence
S Tang, Y Yu, H Wang, G Wang, W Chen… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The computing demand for massive applications has led to the ubiquitous deployment of
computing power. This trend results in the urgent need for higher-level computing resource …
computing power. This trend results in the urgent need for higher-level computing resource …
Dynamic portfolio rebalancing through reinforcement learning
Portfolio managements in financial markets involve risk management strategies and
opportunistic responses to individual trading behaviours. Optimal portfolios constructed aim …
opportunistic responses to individual trading behaviours. Optimal portfolios constructed aim …
Energy efficient task scheduling based on deep reinforcement learning in cloud environment: A specialized review
The expanding scale of cloud data centers and the diversification of user services have led
to an increase in energy consumption and greenhouse gas emissions, resulting in long-term …
to an increase in energy consumption and greenhouse gas emissions, resulting in long-term …
Intent-driven orchestration of serverless applications in the computing continuum
Following the emergence of Internet of Things (IoT) and edge computing technologies and
the development of distributed applications with strict Quality of Service (QoS) requirements …
the development of distributed applications with strict Quality of Service (QoS) requirements …