38040152
Multichannel permutation filters
Vector order statistic based filters designed to exploit the correlation between the channels of a multichannel signal offer improved performance over purely marginal processing. In this paper, the class of permutation filters are extended to handle multichannel signals. Permutation filters are well suited for image processing; they are robust, able to preserve details, and edges in image and video signals, and can also model complicated non-linear systems accurately. Multichannel permutation filters are based on the permutation of a set of sequential observations from a multidimensional process. There exists no unique method for the ranking of vectors, so we evaluate two ranking formulations that preserve characteristics useful in constructing estimators. Simulation results for a video restoration problem are presented.
8225775
A global lower bound on parameter estimation error with periodic distortion functions
We present a global Ziv-Zakai (1969) type lower bound on the mean square error for estimation of signal parameter vectors, where some components of the distortion function may be periodic. Periodic distortion functions arise naturally in the context of direction of arrival or phase estimation problems. The bound is applied to an image registration problem, and compared to the performance of the maximum-likelihood estimator (MLE).
32142802
European VAT on Digital Sales
16902988
A Cost-Sensitive Model for Preemptive Intrusion Response Systems
The proliferation of complex and fast-spreading intrusions not only requires advances in intrusion detection mechanisms but also demands development of sophisticated and automated intrusion response systems. In this paper we present a novel cost-sensitive model for intrusion response that incorporates preemptive deployment of the response actions. Specifically, our technique relies on comparing the cost of deploying a response against the cost of damage caused by an "'un-attended" intrusion and decides to preemptively deploy a response with maximum benefit. Our technique further allows adaptation of responses to the changing environment through evaluation of success and failure of previously triggered responses. We demonstrate the advantages of the approach and evaluate it using a damage reduction metric.
5085726
Uniform quantifier elimination and constraint query processing
Saugata Basu* Mathematical Sciences Research Institute Berkeley, CA 94720, USA
9966669
Resource allocation for remote desktop sessions in Utility Grids
SUMMARY Emerging large scale utility computing systems such as Grids promise computing and storage to be provided to end users as a utility. System management services deployed in the middleware are a key to enabling this vision. Utility Grids provide a challenge in terms of scale, dynamism, and heterogeneity of resources and workloads. In this paper, we present a model based architecture for resource allocation services for Utility Grids. The proposed service is built in the context of interactive remote desktop session workloads and takes application performance QoS models into consideration. The key design guidelines are hierarchical request structure, application performance models, remote desktop session performance models, site admission control, multi-variable resource assignment system, and runtime session admission control. We have also built a simulation framework that can handle mixed batch and remote desktop session requests, and have implemented our proposed resource allocation service into the framework. We present some results from experiments done using the framework. Our proposed architecture for resource allocation services addresses the needs of emerging utility computing systems and captures the key concepts and guidelines for building such services in these environments.
2815801
Architecture for resource allocation services supporting interactive remote desktop sessions in utility grids
Emerging large scale utility computing systems like Grids promise computing and storage to be provided to end users as a utility. System management services deployed in the middleware are a key to enabling this vision. Utility Grids provide a challenge in terms of scale, dynamism, and heterogeneity of resources and workloads. In this paper, we present a model based architecture for resource allocation services for Utility Grids. The proposed service is built in the context of interactive remote desktop session workloads and takes application performance QoS models into consideration. The key design guidelines are hierarchical request structure, application performance models, remote desktop session performance models, site admission control, multi-variable resource assignment system, and runtime session admission control. We have also built a simulation toolkit that can handle mixed batch and remote desktop session requests, and have implemented our proposed resource allocation service into the toolkit. We present some results from experiments done using the toolkit. Our proposed architecture for resource allocation services addresses the needs of emerging utility computing systems and captures the key concepts and guidelines for building such services in these environments.