In recent years, power consumption has become one of the hottest research trends in
computer science and industry. Most of the reasons are related to the operational budget …

In order to reduce the energy consumption in the cloud data center, it is necessary to make
reasonable scheduling of resources in the cloud. The accurate prediction for cloud …

Cloud computing faces many challenges which constitute research problems. The key
challenge is to achieve good resource management that will result in minimum energy …

以Docker 和Kubernetes 为代表的容器云具有额外的资源开销更小, 启动销毁时间更短等优点,
但它仍然存在过度供应和供应不足等资源管理问题. 为了使Kubernetes 集群对部署在其上的 …

Bayesianoptimization (BO) provides an efficient tool for solving the black-box global
optimization problems. Under situations where multiple points can be evaluated …

Availability is one of the most important requirements in production system. Keeping a
persistent level of high availability in the Infrastructure-as-a-Service (IaaS) cloud computing …

Due to the budget and environmental issues, adaptive energy efficiency receives a lot of
attention these days, especially for cloud computing. In the previous research, we developed …

Under the circumstance of big data, traditional storage systems face the big challenge of
energy consumption. Switching some storage nodes, which do not experience workloads, to …

Bayesian-based parallel global optimization methods have become increasingly popular for
solving black-box functions using parallel resources. When the function exhibits …

摘要容器云的发展与应用对资源的高并发, 高可用, 高弹性, 高灵活性等的需求越来越强烈.
在对容器云资源预测问题研究现状进行调查后, 提出一种采用自适应概率的多选择策略遗传算法 …