Dynamic Virtual Resource Management in Clouds Coping with Traffic Burst

Cloud computing is the latest computing paradigm that delivers IT resources as services in which users are free from the burden of worrying about the low-level implementation or system administration details. On the other hand, within the era of information explosion, some websites may encounter a sharp rising workload due to some unexpected social concerns, which make these websites unavailable or even failure. Currently, a post-action method based on human experience and system alarm is widely used to handle this scene in industry, which has shortcomings like reaction delay. In our paper, we want to solve this problem by deploying such websites on cloud, and use features of the cloud to tackle it. We propose a workload forecasting strategy based on Gompertz curve to predict the sharp rising workload, and a customized resource management framework is also proposed to guarantee the high availability of the web applications and energy saving of the cloud service providers. Our experiment first shows the accuracy of our workload forecasting model by using some workload statistics in the real world, and then a simulation-based experiment is designed to indicate that the proposed management framework detects changes in workload intensity that occur over time and allocates multiple virtualized IT resources accordingly to achieve high availability and energy saving targets.