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An Efficient Framework for Scalable Defect Isolation in Large Scale Networks of DNA Self-Assembly

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Abstract

This paper proposes and evaluates an approach for defect isolation of DNA self-assembled networks made of a large number of processing nodes. The complexity of DNA self-assembled networks makes impractical to add a large amount of redundancy and employ inefficient and unscalable defect tolerant schemes. A previous framework based on a broadcast algorithm isolates defective nodes without incorporating redundancy for nodes. However, its disadvantage is the limited scalability, thus making it unsuitable for extremely large scale networks built by DNA self-assembly. The proposed framework improves upon the previous framework by involving three algorithmic tiers; namely, 1-hop wave expansion, efficient via placement, and unsafe node detection. The performance of the proposed framework is evaluated and compared with the original framework by considering large scale networks (up to 2,000 × 2,000 nodes), and a novel gross defect model (as well as a conventional random defect model as assumed in previous works). Simulation results indicate that the proposed framework outperforms the original framework in broadcast latency and efficiency and shows excellent scalability for DNA self-assembled nano-scale networks.

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Correspondence to Masaru Fukushi.

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Responsible Editors: C. Bolchini and Y.-B. Kim

A preliminary version of this paper was published in Proceeding of the IEEE International Symposium on DFT, 2007 [7].

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Fukushi, M., Horiguchi, S., Demoracski, L. et al. An Efficient Framework for Scalable Defect Isolation in Large Scale Networks of DNA Self-Assembly. J Electron Test 25, 11–23 (2009). https://doi.org/10.1007/s10836-008-5086-y

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  • DOI: https://doi.org/10.1007/s10836-008-5086-y

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