To analyze complex and heterogeneous real-time embedded systems, recent works have proposed interface techniques between real-time calculus (RTC) and timed automata (TA), in order to take advantage of the strengths of each technique for analyzing various components. But the time to analyze a state-based component modeled by TA may be prohibitively high, due to the state space explosion problem....

We apply a novel lexicographic framework for bit allocation to the multiplexing of multiple VBR video streams onto a single CBR channel. In the lexico-graphic framework, the maximum distortion is minimized , then the second highest distortion, and so on, resulting in nearly constant quality. With a suitably constructed multiplexing model, we show that the mul-tiplexing problem reduces to a sing...

Object detection and classification are the basic tasks in video analytics and become the starting point for other complex applications. Traditional video analytics approaches are manual and time consuming. These are subjective due to the very involvement of human factor. We present a cloud based video analytics framework for scalable and robust analysis of video streams. The framework empowers...

In this paper we propose a unified framework for decoding and feature representation based on the Maximum A Posterior (MAP) principle. The search space is augmented with an additional feature stream dimension such that different feature representations can be utilized for different phonetic context under the HMM decoding framework. We also provide a theoretic explanation for the unified framewo...

Eavesdroppers can exploit exposed packet headers towards attacks that profile clients and their data flows. In this paper, we propose FOG, a framework for effective header blinding using MIMO, to thwart eavesdroppers. FOG effectively tracks header bits as they traverse physical (PHY) layer sub-systems that perform functions like scrambling and interleaving. It combines multiple blinding signals...

We investigate the problem of deterministic pattern matching in multiple streams. In this model, one symbol arrives at a time and is associated with one of s streaming texts. The task at each time step is to report if there is a new match between a fixed pattern of length m and a newly updated stream. As is usual in the streaming context, the goal is to use as little space as possible while sti...

Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes which serve as features may be divided into classes based on their membership in gene families or pathways. When labeling words with senses for word sense disambiguation, features fall into classes including adjacent wor...

Controlling the quality of collaborative multimedia sessions, that deploy multiple media streams, is a challenging problem. In this paper, we present a framework for achieving quality of session (QoSess) control, focusing on two main components of the QoSess control layer. The first component is a scalable and robust feedback mechanism which allows for determining the worst case state among a g...