Bio-Inspired Quorum Sensing-Based Nanonetwork Synchronization Using Birth-Death Growth Model

Ponsuge Surani Shalika Tissera; Sangho Choe

doi:10.1109/TCOMM.2020.3010992

Bio-Inspired Quorum Sensing-Based Nanonetwork Synchronization Using Birth-Death Growth Model

Ponsuge Surani Shalika Tissera, Sangho Choe

School of Information, Communications and Electronic Engineering

The Catholic University of Korea

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

We construct a bio-inspired nanomachine network via the quorum sensing (QS) mechanism and analyze that nanonetwork from the perspective of global synchronization time and channel capacity. We propose a realistic (stochastic) approach using birth-death-process-based bacterial growth model and compare it to a conventional ideal (deterministic) approach using exponentially-increased bacterial growth model. For the comparative study, we first define a diffusion-based molecular communication channel between bacterial density and autoinducer (AI) concentration as an approximated Gaussian process, and then analyze the presented QS behavior model numerically as well as theoretically. Increases in the bacterial density augment the diffused AI concentration. When the AI concentration satisfies a specified threshold indicating gene expression, almost all bacteria in that colony represent a collective QS behavior such as biofilm formation. Compared to the ideal approach that is simple but not feasible in real life given the limited resources (e.g., food), the realistic approach is complex but better at representing real and probabilistic QS nature, less sensitive at gene expression, and so more suitable for global synchronization analysis. Via simulation, we evaluate the proposed model in terms of AI concentration versus bacterial density, synchronization time, and information sensing capacity, and demonstrate its superiority over the traditional model.

Original language	English
Article number	9145736
Pages (from-to)	6263-6275
Number of pages	13
Journal	IEEE Transactions on Communications
Volume	68
Issue number	10
DOIs	https://doi.org/10.1109/TCOMM.2020.3010992
State	Published - Oct 2020

Bibliographical note

Funding Information:
Manuscript received August 27, 2019; revised January 18, 2020 and May 30, 2020; accepted July 13, 2020. Date of publication July 21, 2020; date of current version October 16, 2020. This work was supported in part by the NRF grant funded by the Korea Government Ministry of Science and ICT (MSIT) under Grant 2017R1A2B4005840, and in part by the Catholic University of Korea, Research Fund, 2019. The associate editor coordinating the review of this article and approving it for publication was M. Wen. (Corresponding author: Sangho Choe.) The authors are with the Department of Information, Communications, and Electronics Engineering, Catholic University of Korea, Bucheon 13557, South Korea (e-mail: [email protected]; [email protected]).

Publisher Copyright:
© 1972-2012 IEEE.

Keywords

autoinducer
bacterial density
birth-death process
capacity
gene expression
molecular communication
nanonetwork
Quorum sensing

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10.1109/TCOMM.2020.3010992

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title = "Bio-Inspired Quorum Sensing-Based Nanonetwork Synchronization Using Birth-Death Growth Model",

abstract = "We construct a bio-inspired nanomachine network via the quorum sensing (QS) mechanism and analyze that nanonetwork from the perspective of global synchronization time and channel capacity. We propose a realistic (stochastic) approach using birth-death-process-based bacterial growth model and compare it to a conventional ideal (deterministic) approach using exponentially-increased bacterial growth model. For the comparative study, we first define a diffusion-based molecular communication channel between bacterial density and autoinducer (AI) concentration as an approximated Gaussian process, and then analyze the presented QS behavior model numerically as well as theoretically. Increases in the bacterial density augment the diffused AI concentration. When the AI concentration satisfies a specified threshold indicating gene expression, almost all bacteria in that colony represent a collective QS behavior such as biofilm formation. Compared to the ideal approach that is simple but not feasible in real life given the limited resources (e.g., food), the realistic approach is complex but better at representing real and probabilistic QS nature, less sensitive at gene expression, and so more suitable for global synchronization analysis. Via simulation, we evaluate the proposed model in terms of AI concentration versus bacterial density, synchronization time, and information sensing capacity, and demonstrate its superiority over the traditional model.",

keywords = "autoinducer, bacterial density, birth-death process, capacity, gene expression, molecular communication, nanonetwork, Quorum sensing",

author = "Tissera, {Ponsuge Surani Shalika} and Sangho Choe",

note = "Funding Information: Manuscript received August 27, 2019; revised January 18, 2020 and May 30, 2020; accepted July 13, 2020. Date of publication July 21, 2020; date of current version October 16, 2020. This work was supported in part by the NRF grant funded by the Korea Government Ministry of Science and ICT (MSIT) under Grant 2017R1A2B4005840, and in part by the Catholic University of Korea, Research Fund, 2019. The associate editor coordinating the review of this article and approving it for publication was M. Wen. (Corresponding author: Sangho Choe.) The authors are with the Department of Information, Communications, and Electronics Engineering, Catholic University of Korea, Bucheon 13557, South Korea (e-mail: [email protected]; [email protected]). Publisher Copyright: {\textcopyright} 1972-2012 IEEE.",

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N2 - We construct a bio-inspired nanomachine network via the quorum sensing (QS) mechanism and analyze that nanonetwork from the perspective of global synchronization time and channel capacity. We propose a realistic (stochastic) approach using birth-death-process-based bacterial growth model and compare it to a conventional ideal (deterministic) approach using exponentially-increased bacterial growth model. For the comparative study, we first define a diffusion-based molecular communication channel between bacterial density and autoinducer (AI) concentration as an approximated Gaussian process, and then analyze the presented QS behavior model numerically as well as theoretically. Increases in the bacterial density augment the diffused AI concentration. When the AI concentration satisfies a specified threshold indicating gene expression, almost all bacteria in that colony represent a collective QS behavior such as biofilm formation. Compared to the ideal approach that is simple but not feasible in real life given the limited resources (e.g., food), the realistic approach is complex but better at representing real and probabilistic QS nature, less sensitive at gene expression, and so more suitable for global synchronization analysis. Via simulation, we evaluate the proposed model in terms of AI concentration versus bacterial density, synchronization time, and information sensing capacity, and demonstrate its superiority over the traditional model.

AB - We construct a bio-inspired nanomachine network via the quorum sensing (QS) mechanism and analyze that nanonetwork from the perspective of global synchronization time and channel capacity. We propose a realistic (stochastic) approach using birth-death-process-based bacterial growth model and compare it to a conventional ideal (deterministic) approach using exponentially-increased bacterial growth model. For the comparative study, we first define a diffusion-based molecular communication channel between bacterial density and autoinducer (AI) concentration as an approximated Gaussian process, and then analyze the presented QS behavior model numerically as well as theoretically. Increases in the bacterial density augment the diffused AI concentration. When the AI concentration satisfies a specified threshold indicating gene expression, almost all bacteria in that colony represent a collective QS behavior such as biofilm formation. Compared to the ideal approach that is simple but not feasible in real life given the limited resources (e.g., food), the realistic approach is complex but better at representing real and probabilistic QS nature, less sensitive at gene expression, and so more suitable for global synchronization analysis. Via simulation, we evaluate the proposed model in terms of AI concentration versus bacterial density, synchronization time, and information sensing capacity, and demonstrate its superiority over the traditional model.

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M1 - 9145736

ER -

Bio-Inspired Quorum Sensing-Based Nanonetwork Synchronization Using Birth-Death Growth Model

Abstract

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Keywords

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