The impact of social behavior on the attenuation and delay of bacterial nanonetworks

Bige D. Unluturk*, Sasitharan Balasubramaniam, Ian F. Akyildiz

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

20 Citations (Scopus)

Abstract

Molecular communication (MC) is a new paradigm for developing communication systems that exchanges information through the transmission and reception of molecules. One proposed model for MC is using bacteria to carry information encoded into DNA plasmids, and this is termed bacterial nanonetworks. However, a limiting factor in the models that have been studied so far is the environment considered only in ideal conditions with a single population. This is far from realistic in natural environments, where bacteria coexist in multiple populations of same and different species, resulting in a very complex social community. This complex community has social interactions that include cooperation, cheating, as well as competition. In this paper, the effects of these social interactions on the information delivery in bacterial nanonetworks are studied in terms of delay, attenuation and data rate. The numerical results show that the cooperative behavior of bacteria improves the performance of delay and attenuation leading to a higher data rate, and this performance can be degraded once their behavior switches towards cheating. The competitive social behavior shows that the performance can degrade delay as well as attenuation leading to slower data rates, as the population with the encoded DNA plasmids are prevented from reaching the receiver. The analysis of social interactions between the bacteria will pave the way for efficient design of bacterial nanonetworks enabling applications such as intrabody sensing, drug delivery, and environmental control against pollution and biological hazards.

Original languageEnglish
Article number7742378
Pages (from-to)959-969
Number of pages11
JournalIEEE Transactions on Nanobioscience
Volume15
Issue number8
DOIs
Publication statusPublished - 1 Dec 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Bacterial social interactions
  • Channel modeling
  • Chemotaxis
  • Molecular communication

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