Self directed learning based workload forecasting model for cloud resource management
Workload prediction plays a vital role in intelligent resource scaling and load balancing that
maximize the economic growth of cloud service providers as well as users' quality of …
maximize the economic growth of cloud service providers as well as users' quality of …
esDNN: deep neural network based multivariate workload prediction in cloud computing environments
Cloud computing has been regarded as a successful paradigm for IT industry by providing
benefits for both service providers and customers. In spite of the advantages, cloud …
benefits for both service providers and customers. In spite of the advantages, cloud …
MAG-D: A multivariate attention network based approach for cloud workload forecasting
The Coronavirus pandemic and the work-from-home have drastically changed the working
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …
Biphase adaptive learning-based neural network model for cloud datacenter workload forecasting
Cloud computing promises elasticity, flexibility and cost-effectiveness to satisfy service level
agreement conditions. The cloud service providers should plan and provision the computing …
agreement conditions. The cloud service providers should plan and provision the computing …
An efficient resource provisioning approach for analyzing cloud workloads: a metaheuristic-based clustering approach
M Ghobaei-Arani, A Shahidinejad - The Journal of Supercomputing, 2021 - Springer
With the recent advancements in Internet-based computing models, the usage of cloud-
based applications to facilitate daily activities is significantly increasing and is expected to …
based applications to facilitate daily activities is significantly increasing and is expected to …
E2LG: a multiscale ensemble of LSTM/GAN deep learning architecture for multistep-ahead cloud workload prediction
P Yazdanian, S Sharifian - The Journal of Supercomputing, 2021 - Springer
Efficient resource demand prediction and management are two main challenges for cloud
service providers in order to control dynamic autoscaling and power consumption in recent …
service providers in order to control dynamic autoscaling and power consumption in recent …
Forecasting Cloud Application Workloads With CloudInsight for Predictive Resource Management
Predictive cloud resource management has been widely adopted to overcome the
limitations of reactive cloud autoscaling. The predictive resource management is highly …
limitations of reactive cloud autoscaling. The predictive resource management is highly …
Auto-adaptive learning-based workload forecasting in dynamic cloud environment
To maintain elasticity and scalability of resources at cloud data centers, future workload
prediction has become an indispensable requirement. However, there is high variance in …
prediction has become an indispensable requirement. However, there is high variance in …
Ensemble learning based predictive framework for virtual machine resource request prediction
The cloud service providers require a large number of computing resources to provide
services on-demand that consume the electricity at large and leave high carbon footprints …
services on-demand that consume the electricity at large and leave high carbon footprints …
Performance evaluation of metaheuristics algorithms for workload prediction in cloud environment
The smooth operation of a cloud data center along with the best user experience is one of
the prime objectives of a resource management scheme that must be achieved at low cost in …
the prime objectives of a resource management scheme that must be achieved at low cost in …