[HTML][HTML] A review of green artificial intelligence: Towards a more sustainable future
Green artificial intelligence (AI) is more environmentally friendly and inclusive than
conventional AI, as it not only produces accurate results without increasing the …
conventional AI, as it not only produces accurate results without increasing the …
Machine learning for cloud security: a systematic review
The popularity and usage of Cloud computing is increasing rapidly. Several companies are
investing in this field either for their own use or to provide it as a service for others. One of …
investing in this field either for their own use or to provide it as a service for others. One of …
Resource provisioning using workload clustering in cloud computing environment: a hybrid approach
In recent years, cloud computing paradigm has emerged as an internet-based technology to
realize the utility model of computing for serving compute-intensive applications. In the cloud …
realize the utility model of computing for serving compute-intensive applications. In the cloud …
A resource utilization prediction model for cloud data centers using evolutionary algorithms and machine learning techniques
Cloud computing has revolutionized the modes of computing. With huge success and
diverse benefits, the paradigm faces several challenges as well. Power consumption …
diverse benefits, the paradigm faces several challenges as well. Power consumption …
An energy aware resource allocation based on combination of CNN and GRU for virtual machine selection
The use of cloud computing service models is rapidly increasing, but inefficient resource
usage in cloud data centers can lead to great energy consumption and costs. To address …
usage in cloud data centers can lead to great energy consumption and costs. To address …
Deepscaling: microservices autoscaling for stable cpu utilization in large scale cloud systems
Cloud service providers conservatively provision excessive resources to ensure service
level objectives (SLOs) are met. They often set lower CPU utilization targets to ensure …
level objectives (SLOs) are met. They often set lower CPU utilization targets to ensure …
Burst-aware predictive autoscaling for containerized microservices
Autoscaling methods are used for cloud-hosted applications to dynamically scale the
allocated resources for guaranteeing Quality-of-Service (QoS). The public-facing application …
allocated resources for guaranteeing Quality-of-Service (QoS). The public-facing application …
CEC: A containerized edge computing framework for dynamic resource provisioning
Container has been widely used in application development and management systems.
However, there are two major challenges faced in the real deployment at edge servers. The …
However, there are two major challenges faced in the real deployment at edge servers. The …
Robustscaler: Qos-aware autoscaling for complex workloads
Autoscaling is a critical component for efficient resource utilization with satisfactory quality of
service (QoS) in cloud computing. This paper investigates proactive autoscaling for widely …
service (QoS) in cloud computing. This paper investigates proactive autoscaling for widely …
A deep learning-based resource usage prediction model for resource provisioning in an autonomic cloud computing environment
MS Al-Asaly, MA Bencherif, A Alsanad… - Neural Computing and …, 2022 - Springer
Cloud computing enables clients to acquire cloud resources dynamically and on demand for
their cloud applications and services. For cloud providers, especially, Software as a Service …
their cloud applications and services. For cloud providers, especially, Software as a Service …