Characterization and comparison of cloud versus grid workloads
A new era of Cloud Computing has emerged, but the characteristics of Cloud load in data
centers is not perfectly clear. Yet this characterization is critical for the design of novel Cloud …
centers is not perfectly clear. Yet this characterization is critical for the design of novel Cloud …
Characterizing machines and workloads on a Google cluster
Cloud computing offers high scalability, flexibility and cost-effectiveness to meet emerging
computing requirements. Understanding the characteristics of real workloads on a large …
computing requirements. Understanding the characteristics of real workloads on a large …
Moneyball: proactive auto-scaling in Microsoft Azure SQL database serverless
Microsoft Azure SQL Database is among the leading relational database service providers
in the cloud. Serverless compute automatically scales resources based on workload …
in the cloud. Serverless compute automatically scales resources based on workload …
Characteristics of co-allocated online services and batch jobs in internet data centers: a case study from Alibaba cloud
In order to reduce power and energy costs, giant cloud providers now mix online and batch
jobs on the same cluster. Although the co-allocation of such jobs improves machine …
jobs on the same cluster. Although the co-allocation of such jobs improves machine …
Toward ml-centric cloud platforms
Toward ML-centric cloud platforms Page 1 50 COMMUNICATIONS OF THE ACM | FEBRUARY
2020 | VOL. 63 | NO. 2 contributed articles IMA GE B Y MARCEL CLEMENS resource …
2020 | VOL. 63 | NO. 2 contributed articles IMA GE B Y MARCEL CLEMENS resource …
A meta reinforcement learning approach for predictive autoscaling in the cloud
Predictive autoscaling (autoscaling with workload forecasting) is an important mechanism
that supports autonomous adjustment of computing resources in accordance with fluctuating …
that supports autonomous adjustment of computing resources in accordance with fluctuating …
Take it to the limit: peak prediction-driven resource overcommitment in datacenters
To increase utilization, datacenter schedulers often overcommit resources where the sum of
resources allocated to the tasks on a machine exceeds its physical capacity. Setting the right …
resources allocated to the tasks on a machine exceeds its physical capacity. Setting the right …
DRL-scheduling: An intelligent QoS-aware job scheduling framework for applications in clouds
Y Wei, L Pan, S Liu, L Wu, X Meng - IEEE access, 2018 - ieeexplore.ieee.org
As an increasing number of traditional applications migrated to the cloud, achieving
resource management and performance optimization in such a dynamic and uncertain …
resource management and performance optimization in such a dynamic and uncertain …
A deep learning approach for VM workload prediction in the cloud
F Qiu, B Zhang, J Guo - 2016 17th IEEE/ACIS International …, 2016 - ieeexplore.ieee.org
In order to manage the resources in cloud efficiently, ensure the performance of cloud
services and reduce the power consumption, it is critical to predict the workload of virtual …
services and reduce the power consumption, it is critical to predict the workload of virtual …
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 …