Biblio

Cloud computing is an innovative mechanism to optimize computing and storage resource utilization. Due to its cost-saving, high-efficiency advantage, the technology receives wide adoption from IT industries. However, the frequent emergences of security events become the heaviest obstacle for its advancement. The multi-layer and distributive characteristics of cloud computing make IT admins compulsively collect all necessary situational information at cloud runtime if they want to grasp the panoramic secure state, hereby practice configuration management and emergency response methods when necessary. On the other hand, technologies such as elastic resource pooling, dynamic load balancing and virtual machine real-time migration complicate the difficulty of data gathering, where secure information may come from virtual machine hypervisor, network accounting or host monitor proxies. How to classify, arrange, standardize and visualize these data turns into the most crucial issue for cloud computing security situation awareness and presentation. This dissertation borrows traditional fashion of data visualization to integrate into cloud computing features, proposes a new method for aggregating and displaying secure information which IT admins concern, and expects that by method realization cloud security monitor/management capabilities could be notably enhanced.

This paper investigates several techniques that increase the accuracy of motion boundaries in estimated motion fields of a local dense estimation scheme. In particular, we examine two matching metrics, one is MSE in the image domain and the other one is a recently proposed multiresolution metric that has been shown to produce more accurate motion boundaries. We also examine several different edge-preserving filters. The edge-aware moving average filter, proposed in this paper, takes an input image and the result of an edge detection algorithm, and outputs an image that is smooth except at the detected edges. Compared to the adoption of edge-preserving filters, we find that matching metrics play a more important role in estimating accurate and compressible motion fields. Nevertheless, the proposed filter may provide further improvements in the accuracy of the motion boundaries. These findings can be very useful for a number of recently proposed scalable interactive video coding schemes.