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Optimal Scheduling of Biochemical Analyses on Digital Microfluidic Systems
 

Summary: Optimal Scheduling of Biochemical Analyses on
Digital Microfluidic Systems
Lingzhi Luo and Srinivas Akella
Abstract-- Digital microfluidic systems (DMFS) are an
emerging class of lab-on-a-chip systems that manipulate in-
dividual droplets of chemicals on a planar array of electrodes.
The biochemical analyses are performed by repeatedly moving,
mixing, and splitting droplets on the electrodes. In this paper,
we focus on minimizing the completion time of biochemical
analyses by exploiting the parallelism among the operations.
We consider a binary tree representation of chemical analyses
to schedule operations. Using pipelining, we overlap mixing
operations with input and transportation operations. We find
the lower bound of the mixing completion time according to
the tree structure of given reactions, and calculate the minimal
number of mixers S required to achieve the lower bound. We
present a scheduling algorithm for the case with a specified
number of mixers no more than S, and prove it is optimal to
minimize the mixing completion time. We also analyze resource
constraint issues for two extreme cases. For the case with one

  

Source: Akella, Srinivas - Department of Computer Science, University of North Carolina, Charlotte

 

Collections: Engineering; Computer Technologies and Information Sciences