History has demonstrated that healthcare and medical systems play a crucial role in
enforcing the development of science and technology. Humans have been seeing an …

Storage workload prediction is a critical step for fine-grained load balancing and job
scheduling in realtime and adaptive cluster systems. However, how to perform workload …

Cloud workload turning point is either a local peak point standing for workload pressure or a
local valley point standing for resource waste. Predicting such critical points is important to …

Abstract System logs which trace system states and record valuable events comprise a
significant component of any computer system in our daily life. There exist abundant …

This study aims to identify the most effective input parameters for performance modelling of
container-based web systems. We introduce a method using queueing Petri nets to model …

Accurate prediction on the utilization of cloud resources is increasingly important for public
cloud users, as it relates to the reasonable reservation of resources for minimizing the usage …

Accurate storage workload forecasting of big data applications is a constructive approach to
improve the job scheduling and fine-grained load balancing in real-time cluster systems …

The complexity of apps running on cloud platforms is evident in their nature. Every
application has distinct needs for processing power and memory at various times. In order to …

In this study, support vector machine (SVM) and back-propagation (BP) neural networks
were combined to predict the workload of cloud computing physical machine, so as to …

Low latency and high availability in cloud services give users satisfactory response time and
guarantee stability to request they make to services that are hosted in the cloud, thus …