Abstract-Due to recent advances in microfluidics, digital microfluidic biochips are expected to revolutionize laboratory procedures. One critical problem for biochip synthesis is the droplet routing problem. Unlike traditional very large scale integration routing problems, in addition to routing path selection, the biochip routing problem needs to address the issue of scheduling droplets under practical constraints imposed by the fluidic property and timing restriction of synthesis results. In this paper, we present the first network-flow-based routing algorithm that can concurrently route a set of noninterfering nets for the droplet routing problem on biochips. We adopt a two-stage technique of global routing followed by detailed routing. In global routing, we first identify a set of noninterfering nets and then adopt the network-flow approach to generate optimal global-routing paths for nets. In detailed routing, we present the first polynomial-time algorithm for simultaneous routing and scheduling using the global-routing paths with a negotiation-based routing scheme. Our algorithm targets at both the minimization of cells used for routing for better fault tolerance and minimization of droplet transportation time for better reliability and faster bioassay execution. Experimental results show the robustness and efficiency of our algorithm.Index Terms-Detailed routing, digital microfluidic biochips, global routing, network-flow-based algorithm.
Droplet-based microfluidic biochips have recently gained much attention and are expected to revolutionize the biological laboratory procedure. As biochips are adopted for the complex procedures in molecular biology, its complexity is expected to increase due to the need of multiple and concurrent assays on a chip. In this paper, we formulate the placement problem of digital microfluidic biochips with a tree-based topological representation, called T-tree. To the best knowledge of the authors, this is the first work that adopts a topological representation to solve the placement problem of digital microfluidic biochips. Experimental results demonstrate that our approach is much more efficient and effective, compared with the previous unified synthesis and placement framework.
Droplet-based microfluidic biochips have recently gained much attention and are expected to revolutionize the biological laboratory procedures. As biochips are adopted for the complex procedures in molecular biology, its complexity is expected to increase due to the need of multiple and concurrent assays on a chip. In this article, we formulate the placement problem of digital microfluidic biochips with a tree-based topological representation, called T-tree. To the best knowledge of the authors, this is the first work that adopts a topological representation to solve the placement problem of digital microfluidic biochips. We also consider the defect tolerant issue to avoid to use defective cells due to fabrication. Experimental results demonstrate that our approach is more efficient and effective than the previous unified synthesis and placement framework.
Due to recent advances in microfluidics technology, digital microfluidic biochips and their associated CAD problems have gained much attention, most of which has been devoted to direct-addressing biochips. In this paper, we solve the droplet routing problem under the more scalable crossreferencing biochip paradigm, which uses row/column addressing scheme to activate electrodes. We propose the first droplet routing algorithm that directly solves the problem of routing in cross-referencing biochips. The main challenge of this type of biochips is the electrode interference which prevents simultaneous movement of multiple droplets. We first present a basic integer linear programming (ILP) formulation to optimally solve the droplet routing problem. Due to its complexity, we also propose a progressive ILP scheme to determine the locations of droplets at each time step. Experimental results demonstrate the efficiency and effectiveness of our progressive ILP scheme on a set of practical bioassays.
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