When bacteria talk: Time elapse communication for super-slow networks

Krishnaswamy, Bhuvana; Henegar, Caitlin; Bardill, J. Patrick; Russakow, Daniel; Holst, Gregory L.; Hammer, Brian K.; Forest, Craig R.; Sivakumar, R.

doi:10.1109/icc.2013.6655625

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…where (61) holds due to (4), and (62) follows due to (5). Since the server processes the packets independent of the arrival process, S i is independent of A ∞ 1 , D i−1 0 , W i−1 , and thus (63) holds.…”

Section: A Achievability For the M/m/1 Queuementioning

confidence: 99%

“…Timing channels convey information by the timing of consecutive packets -rather than by their contents. Such channels not only arise in many engineering contexts, such as covert communications [1], [2] and sensor networks [3], but can also provide a reasonable abstraction of interactions in biological systems [4]. In addition, information theoretic understanding of timing channels can potentially help us attack the challenging problem of causal inference in systems where causal relationships are determined by timing information [5], [6].…”

Section: Introductionmentioning

confidence: 99%

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Bits through bufferless queues

Tavan

Yates

Bajwa

2013

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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This paper investigates the capacity of a channel in which information is conveyed by the timing of consecutive packets passing through a queue with independent and identically distributed service times. Such timing channels are commonly studied under the assumption of a work-conserving queue. In contrast, this paper studies the case of a bufferless queue that drops arriving packets while a packet is in service. Under this bufferless model, the paper provides upper bounds on the capacity of timing channels and establishes achievable rates for the case of bufferless M/M/1 and M/G/1 queues. In particular, it is shown that a bufferless M/M/1 queue at worst suffers less than 10% reduction in capacity when compared to an M/M/1 work-conserving queue.Since W i−1 = W i−1 (U, D i−1 0 ) is a deterministic function of

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Section: A Achievability For the M/m/1 Queuementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bits through bufferless queues

Tavan

Yates

Bajwa

2013

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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“…An "arabinose pulse" is the duration and concentration over which this arabinose inducer is delivered to the transmitter bacterial chamber. Pulse durations of 50 min and concentrations of 20 lM that we have previously optimized for stimulus 15,25 were used. Fluorescent images were captured once in every 10 min at 20Â magnification and post-processed using MATLAB.…”

Section: E Bacterial Communicationmentioning

confidence: 99%

Porous monolith microfluidics for bacterial cell-to-cell communication assays

et al. 2017

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Genetically engineered bacteria can be used for a wide range of applications, from monitoring environmental toxins to studying complex communication networks in the human digestive system. Although great strides have been made in studying single strains of bacteria in well-controlled microfluidic environments, there remains a need for tools to reliably control and measure communication between multiple discrete bacterial populations. Stable long-term experiments (e.g., days) with controlled population sizes and regulated input (e.g., concentration) and output measurements can reveal fundamental limits of cell-to-cell communication. In this work, we developed a microfluidic platform that utilizes a porous monolith to reliably and stably partition adjacent strains of bacteria while allowing molecular communication between them for several days. We measured small molecule production by the bacterial populations in response to stimuli using analytical chemistry methods and measured fluorescent output. The results are compared with communication and diffusion delay models. This porous monolith microfluidic system enables bacterial cell-to-cell communication assays with dynamic control of inputs, relatively long-term experimentation with no cross contamination, and stable bacterial population size. This system can serve as a valuable tool in understanding bacterial communication and improving biosensor design capabilities.

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“…For example, a QS-based theoretical MC system using bacteria as the transceivers is proposed in [15]. For bio-inspired MC system in [16], [17], bacteria are used as information carriers and QS is considered at the receiver. In [18], an externally controllable biological MC testbed using Escherichia coli (E. coli) bacteria is described.…”

Section: Introductionmentioning

confidence: 99%

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System

Bai

Zhu

et al. 2023

IEEE Trans.on Nanobioscience

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Molecular communication (MC) aims to use signaling molecules as information carriers to achieve communication between biological entities. However, MC systems severely suffer from inter symbol interference (ISI) and external noise, making it virtually difficult t o obtain accurate mathematical models. Specifically, the mathematically intractable channel state information (CSI) of MC motivates the deep learning (DL) based signal detection methods. In this paper, a modified t emporal convolutional network (TCN) is proposed for signal detection for a special MC communication system which uses magnetotactic bacteria (MTB) as information carriers. Results show that the TCN-based detector demonstrates the best overall performance. In particular, it achieves better bit error rate (BER) performance than sub-optimal maximum a posteriori (MAP) and deep neural network (DNN) based detectors. However, it behaves similar with the bidirectional long short term memory (BiLSTM) based detector that have been previously proposed and worse than the optimal MAP detector. When both BER performance and computational complexity are taken into account, the proposed TCN-based detector outperforms BiLSTM-based detectors. Furthermore, in terms of robustness evaluation, the proposed TCN-based detector outperforms all other DL-based detectors.

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When bacteria talk: Time elapse communication for super-slow networks

Cited by 9 publications

References 15 publications

Bits through bufferless queues

Bits through bufferless queues

Porous monolith microfluidics for bacterial cell-to-cell communication assays

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System

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