Model-Based Assistance for Making Time/Fidelity Trade-Offs in Component Compositions

Abstract

Abstract-In many scientific fields, simulations and analyses require compositions of computational entities such as webservices, programs, and applications. In such fields, users may want various trade-offs between different qualities. Examples include: (i) performing a quick approximation vs. an accurate, but slower, experiment, (ii) using local slower execution environments vs. remote, but advanced, computing facilities, (iii) using quicker approximation algorithms vs. computationally expensive algorithms with smaller data. However, such trade-offs are difficult to make as many such decisions today are either (a) wired into a fixed configuration and cannot be changed, or (b) require detailed systems knowledge and experimentation to determine what configuration to use. In this paper we propose an approach that uses architectural models coupled with automated design space generation for making fidelity and timeliness trade-offs. We illustrate this approach through an example in the intelligence analysis domain.

HaiQ

“…These and other approaches in systems engineering (e.g., [42]) can optimize quantitative aspects of designs, but do not support structural synthesis. Other approaches [6,21] combine structural synthesis with simulation and dynamic analysis to provide estimates of quantitative properties of design variants. These approaches share with ours the idea of synthesizing a solution space from a set of constraints and analyzing individual solutions independently.…”

“…Recent product line reliability analysis approaches [16,17,26,41] improve on exibility by introducing systematic treatment of variability, but are not equipped to synthesize or explore complex structures, and lack languages tailored to check sophisticated properties across design spaces (i.e., temporal logics employed like PCTL [38] can capture properties only about a single model, not collections of individual variants). Other works in quantitative optimization of architectures [3,6,8,10,11,21,22,29,44,45] can in some cases synthesize complex structures [6,21], but are not compatible with formal verication and can only provide estimates of probabilistic properties that could dier from actual guarantees (e.g., worst case) available only via exhaustive state-space exploration.…”