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Record W2990481102 · doi:10.1109/icc40277.2020.9148728

Toward a Wired Ad Hoc Nanonetwork

2020· preprint· en· W2990481102 on OpenAlexaff
Oussama Abderrahmane Dambri, Soumaya Cherkaoui

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMolecular communicationWireless ad hoc networkThroughputComputer scienceWirelessComputer networkPhysical layerVehicular ad hoc networkDistributed computingChannel (broadcasting)Telecommunications

Abstract

fetched live from OpenAlex

Nanomachines promise to enable new medical applications, including drug delivery and real time chemical reactions' detection inside the human body. Such complex tasks need cooperation between nanomachines using a communication network. Wireless Ad hoc networks, using molecular or electromagnetic-based communication have been proposed in the literature to create flexible nanonetworks between nanomachines. In this paper, we propose a Wired Ad hoc NanoNETwork (WANNET) model design using actin-based nano-communication. In the proposed model, actin filaments self-assembly and disassembly is used to create flexible nanowires between nanomachines, and electrons are used as carriers of information. We give a general overview of the application layer, Medium Access Control (MAC) layer and a physical layer of the model. We also detail the analytical model of the physical layer using actin nanowire equivalent circuits, and we present an estimation of the circuit component's values. Numerical results of the derived model are provided in terms of attenuation, phase and delay as a function of the frequency and distances between nanomachines. The maximum throughput of the actin-based nanowire is also provided, and a comparison between the maximum throughput of the proposed WANNET, vs other proposed approaches is presented. The obtained results prove that the proposed wired ad hoc nanonetwork can give a very high achievable throughput with a smaller delay compared to other proposed wireless molecular communication networks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.230
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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