Synthesis of reliable digital microfluidic blochips using Monte Carlo simulation

Microfluidic-based biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis using microfluidics. The "digital microfluidic" biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets (hence the term "digital"), and thus are highly reconfigurable and scalable. We model a biochemical application using an abstract model consisting of a sequencing graph. The digital biochip is modeled as a two-dimensional array of cells, where each cell can hold a droplet. In this paper we propose an integer linear programming (ILP) synthesis methodology that, starting from a biochemical application and a given biochip, determines the allocation, placement, resource binding, and scheduling of the operations in the application. Our goal is to find that particular implementation of an application onto a biochip, which has the highest probability to be reconfigured successfully in case of multiple faulty cells. We propose a fault model for biochips, and use Monte Carlo simulation to evaluate the probability of successful reconfiguration of each implementation in case of faults. The proposed methodology has been evaluated using a real-life example.