Distributed computation with continual population growth.
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| Title: | Distributed computation with continual population growth. |
|---|---|
| Authors: | Cho, Da-Jung1 (AUTHOR), Függer, Matthias2 (AUTHOR), Hopper, Corbin3,4 (AUTHOR), Kushwaha, Manish5 (AUTHOR), Nowak, Thomas4 (AUTHOR) thomas.nowak@lri.fr, Soubeyran, Quentin4,6 (AUTHOR) |
| Source: | Distributed Computing. Dec2022, Vol. 35 Issue 6, p547-569. 23p. |
| Subjects: | NAND gates, Flow simulations |
| Abstract: | Computing via synthetically engineered bacteria is a vibrant and active field with numerous applications in bio-production, bio-sensing, and medicine. Motivated by the lack of robustness and by resource limitation inside single cells, distributed approaches with communication among bacteria have recently gained in interest. In this paper, we focus on the problem of population growth happening concurrently, and possibly interfering, with the desired bio-computation. Specifically, we present a fast protocol in systems with continuous population growth for the majority consensus problem and prove that it correctly identifies the initial majority among two inputs with high probability if the initial difference is Ω (n log n) where n is the total initial population. We also present a fast protocol that correctly computes the Nand of two inputs with high probability. By combining Nand gates with the majority consensus protocol as an amplifier, it is possible to compute arbitrary Boolean functions. Finally, we extend the protocols to several biologically relevant settings. We simulate a plausible implementation of a noisy Nand gate with engineered bacteria. In the context of continuous cultures with a constant outflow and a constant inflow of fresh media, we demonstrate that majority consensus is achieved only if the flow is slower than the maximum growth rate. Simulations suggest that flow increases consensus time over a wide parameter range. The proposed protocols help set the stage for bio-engineered distributed computation that directly addresses continuous stochastic population growth. [ABSTRACT FROM AUTHOR] |
| Copyright of Distributed Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 159957935 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Distributed computation with continual population growth. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cho%2C+Da-Jung%22">Cho, Da-Jung</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Függer%2C+Matthias%22">Függer, Matthias</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hopper%2C+Corbin%22">Hopper, Corbin</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kushwaha%2C+Manish%22">Kushwaha, Manish</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nowak%2C+Thomas%22">Nowak, Thomas</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> thomas.nowak@lri.fr</i><br /><searchLink fieldCode="AR" term="%22Soubeyran%2C+Quentin%22">Soubeyran, Quentin</searchLink><relatesTo>4,6</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Distributed+Computing%22">Distributed Computing</searchLink>. Dec2022, Vol. 35 Issue 6, p547-569. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22NAND+gates%22">NAND gates</searchLink><br /><searchLink fieldCode="DE" term="%22Flow+simulations%22">Flow simulations</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Computing via synthetically engineered bacteria is a vibrant and active field with numerous applications in bio-production, bio-sensing, and medicine. Motivated by the lack of robustness and by resource limitation inside single cells, distributed approaches with communication among bacteria have recently gained in interest. In this paper, we focus on the problem of population growth happening concurrently, and possibly interfering, with the desired bio-computation. Specifically, we present a fast protocol in systems with continuous population growth for the majority consensus problem and prove that it correctly identifies the initial majority among two inputs with high probability if the initial difference is Ω (n log n) where n is the total initial population. We also present a fast protocol that correctly computes the Nand of two inputs with high probability. By combining Nand gates with the majority consensus protocol as an amplifier, it is possible to compute arbitrary Boolean functions. Finally, we extend the protocols to several biologically relevant settings. We simulate a plausible implementation of a noisy Nand gate with engineered bacteria. In the context of continuous cultures with a constant outflow and a constant inflow of fresh media, we demonstrate that majority consensus is achieved only if the flow is slower than the maximum growth rate. Simulations suggest that flow increases consensus time over a wide parameter range. The proposed protocols help set the stage for bio-engineered distributed computation that directly addresses continuous stochastic population growth. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Distributed Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00446-021-00404-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 547 Subjects: – SubjectFull: NAND gates Type: general – SubjectFull: Flow simulations Type: general Titles: – TitleFull: Distributed computation with continual population growth. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cho, Da-Jung – PersonEntity: Name: NameFull: Függer, Matthias – PersonEntity: Name: NameFull: Hopper, Corbin – PersonEntity: Name: NameFull: Kushwaha, Manish – PersonEntity: Name: NameFull: Nowak, Thomas – PersonEntity: Name: NameFull: Soubeyran, Quentin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 01782770 Numbering: – Type: volume Value: 35 – Type: issue Value: 6 Titles: – TitleFull: Distributed Computing Type: main |
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