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Fig. 2.23 Comparison between the completion time of reliability-driven and reliability-oblivious
error-recovery [ 17 ]whena1
4 defect array is injected in exponential dilution. The error bars
show the maximum and minimum completion time for reliability-oblivious error-recovery in the
simulation
reduces the bioassay completion time. At the same time, we avoid the problem that
any given set of defective electrodes can lead to replicated errors, thus the number of
errors in the bioassay is reduced and the reliability for the experiment is improved.
As less reagents/samples are consumed, the cost of the experiment is reduced.
2.6
Chapter Summary and Conclusions
In this chapter, we have shown how recent advances in the integration of a
sensing system in a digital microfluidics biochip can be implemented to make
biochips error-resilient. We have presented a cyberphysical approach for “physical-
aware” system reconfiguration that uses sensor data at intermediate checkpoints to
dynamically reconfigure the biochip. Real-time experiment monitory techniques
based on integrated optical detector and CCD camera have been considered. Two
different sensor-driven re-synthesis techniques have been developed to dynamically
generate new schedules, module placements, and droplet routing pathways for
the bioassay, with minimum impact on the time-to-response. These two methods
have been evaluated and compared in terms of bioassay completion time and CPU
time needed for re-synthesis. The coordination between the physical-aware control
software and the microfluidic biochip allows sensor data to be used as feedback
to make decisions about completed operations, to optimize electrode actuation
sequences for subsequent operations, and to dynamically reconfigure the biochip.
The proposed approach has been evaluated through simulation and its effectiveness
demonstrated for three representative protein bioassays.
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