The bioinformatics software domain contains thousands of applications for automating tasks such as the pairwise alignment of DNA sequences, building and reasoning about metabolic models or simulating growth of an organism. Its end users range from sophisticated developers to those with little computational experience. In response to their needs, developers provide many options to customize the way their algorithms are tuned. Yet there is little or no automated help for the user in determining the consequences or impact of the options they choose. In this paper we describe our experience working with configurable bioinformatics tools. We find limited documentation and help for combining and selecting options along with variation in both functionality and performance. We also find previously undetected faults. We summarize our findings with a set of lessons learned, and present a roadmap for creating automated techniques to interact with bioinformatics software. We believe these will generalize to other types of scientific software.

We adopt an optimization framework for the rate allocation problem proposed by Kelly and investigate the stability of a discretized system with arbitrary communication delays between network elements. We show that there is an underlying market structure, and the stability of this market equilibrium is directly related to the stability of the rate control system. We first derive general stability conditions and use them to establish the stability of the system with a family of popular utility and resource price functions. Numerical examples are provided to validate our analyses.

This work develops a discrete-time dynamical feedback system model for a simplified TCP network with RED control and provides a nonlinear analysis that can help in understanding observed parametric sensitivities. The model describes network dynamics over large parameter variations. The dynamical model is used to analyze the TCP-RED operating point and its stability with respect to various RED controller and system parameters. Bifurcations are shown to occur as system parameters are varied. These bifurcations, which involve the emergence of oscillatory and/or chaotic behavior, shed light on the parametric sensitivity observed in practice. The bifurcations arise due to the presence of a nonlinearity in the TCP throughput characteristic as a function of drop probability at the gateway. Among the bifurcations observed in the system are period doubling and border collision bifurcations. The bifurcations are studied analytically, numerically, and experimentally.

This work develops a discrete time feedback system model for a simplified TCP (transmission control protocol) network with RED (random early detection) control. The model involves sampling the buffer occupancy variable at certain instants. The dynamical model is used to analyze the TCP-RED operating point and its stability with respect to various RED controller and system parameters. Bifurcations are shown to occur as various system parameters are varied. These bifurcations, which involve the emergence of oscillatory and/or chaotic behavior, may provide an explanation for the parameter sensitivity observed in practice. The bifurcations arise due to the presence of a nonlinearity in the characteristics of TCP throughput as a function of drop probability at the gateway. Among the bifurcations observed in the system are the period-doubling bifurcation and border collision bifurcations. The bifurcations are studied analytically, numerically, and experimentally.