On Modeling Information Spreading in Bacterial Nano-Networks Based on Plasmid Conjugation

In the last years, nano-communications have attracted much attention as a newly promising research field. In particular, molecular communications, which exploit molecular nodes, are a powerful tool to implement communication functionalities in environments where the use of electromagnetic waves becomes critical, e.g., in the human body. In molecular communications, molecules such as proteins, DNA and RNA sequences are used to carry information. To this aim a novel approach relies on the use of genetically modified bacteria to transport enhanced DNA strands, called plasmids, where information can be encoded. Information transfer is thus based on bacteria motility, i.e., self-propelled motion, which under appropriate circumstances is exhibited by certain bacteria. It has been observed that bacteria motility presents many similarities with opportunistic forwarding. Currently the few studies on opportunistic communications among bacteria are based on simulations only. In this paper we propose an analytical model to characterize information spreading in bacterial nano-networks. To this purpose, an epidemic approach, similar to those used to model Delay Tolerant Networks (DTNs), is employed. We also derive two mathematical models which slightly differ. The first describes bacterial nano-networks where a single plasmid is disseminated according to an epidemic approach; the second, takes into account more complex mechanisms where multiple plasmids are disseminated as in realistic bacterial nano-networks. Numerical results being obtained are finally shown and discussed.