Prediction-based Federated Management of Multi-scale Resources in Cloud

The connotation of the cloud resources have been extended to be multi-scale resources, which includes central resources as presented by data center, edge resources as presented by Content Delivery Network (CDN) and end resources as presented by Peer-to-Peer (P2P). Under the development situation of the scale of the cloud services, it is difficult to provide services (e.g. streaming distribution) with guaranteed QoS only relying on single type of resource (e.g. central resources) to geo-distributed users. Therefore, making multi-resources cooperative to provide reliable services is necessary. However, it is a great challenge to realize Federated Management of Multi-scale Resources (FMMR). In this research, we propose the idea of prediction-based FMMR, and present the problem formulation introducing economic profit from the perspective of CDN operators. Then, we present the method of Time-series Prediction based on Wavelet Analysis (TPWA) to predict the resource requirements of streaming cloud services in CDN. Finally, the predictability of the resource requirement pattern of the streaming cloud service and the effectiveness of our proposed method have been verified, based on the traces collected from a real CDN entity.