Middleware Support for Aperiodic Tasks in Distributed Real-Time Systems

Many mission-critical distributed real-time applications must handle aperiodic tasks with end-to-end deadlines. However, existing middleware (e.g., RT-CORBA) lacks schedulability analysis and run-time enforcement mecha-nisms needed to give online real-time guarantees for ape-riodic tasks. The primary contribution of this work is the design, implementation, and performance evaluation of the first realization of deferrable server and admission control mechanisms for aperiodic tasks in middleware. Empirical results on a KURT-Linux testbed demonstrate the efficiency and effectiveness of our deferrable server and admission control mechanisms in TAO’s federated event service.

Customizing Component Middleware for Distributed Real-Time Systems with Aperiodic and Periodic Tasks

Many distributed real-time applications must handle mixed aperiodic and periodic tasks with diverse requirements. However, existing middleware lacks flexible configuration mechanisms needed to manage end-to-end timing easily for a wide range of different applications with both aperiodic and periodic tasks. The primary contribution of this work is the design, implementation and performance evaluation of the first configurable component middleware services for admission control and load balancing of aperiodic and periodic tasks in distributed real-time systems. Empirical results demonstrate the need for, and the effectiveness of, our configurable component middleware approach in supporting different applications with aperiodic and periodic tasks

Roadmap Analysis of Protein-Protein Interactions. Master\u27s Thesis, August 2007

The ability to effectively model the interaction between proteins is an important and open problem. In molecular biology it is well accepted that from sequence arises form and from form arises function but relating structure to function remains a challenge. The function of a given protein is defined by its interactions. Likewise a malfunction or a change in protein-protein interactions is a hallmark of many diseases. Many researchers are studying the mechanisms of protein-protein interactions and one of the overarching goals of the community is to predict whether two proteins will bind, and if so what the final conformation will be. Attention is seldom paid to the association pathways that allow two proteins to bind. Evidence has shown that the information in the association pathways can play a vital role in understanding the interaction itself. This thesis presents a novel and scalable approach to computing association pathways between two proteins using the Probabilistic Roadmap (PRM) framework. We will discuss the challenges in extending PRM to the domain of protein-protein interactions such as performing structural mappings in a reduced space of flexibility, and sampling high dimensional conformation spaces. We will present analysis of individual association pathways as well as methods for estimating collective properties of the energy landscape. Our results indicate that these methods can discriminate between true and false protein binding interfaces. Finally, we will present condensing methods such as pathway clustering and visualization using dimensionality reduction that can be be applied to create compact representations of the interaction space

Middleware Support for Aperiodic Tasks in Distributed Real-Time Systems

Many mission-critical distributed real-time applications must handle aperiodic tasks with end-to-end deadlines. However, existing middleware (e.g., RT-CORBA) lacks schedulability analysis and run-time enforcement mechanisms needed to give online real-time guarantees for aperiodic tasks. The primary contribution of this work is the design, implementation, and performance evaluation of the first realization of deferrable server and admission control mechanisms for aperiodic tasks in middleware. Empirical results on a KURT-Linux testbed demonstrate the efficiency and effectiveness of our deferrable server and admission control mechanisms in TAO’s federated event service