Page 123 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 3 – Internet of Bio-Nano Things for health applications

ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 3

EVOLUTIONARY GAME THEORETIC RESOURCE ALLOCATION SIMULATION FOR MOLECULAR
COMMUNICATION

2
1
Caglar Koca , Meltem Civas , Ozgur B. Akan 1,2
2
1 Internet of Everthing (IoE) Group, Department of Engineering, University of Cambridge, UK , Next‑generation and
Wireless Communications Laboratory (NWCL), Department of Electrical and Electronics Engineering, Koç University,
Istanbul, Turkey
NOTE: Corresponding author: Caglar Koca, ck542@cam.ac.uk

Abstract – Molecular Communication (MC) is an emerging technology using molecules to transfer information between
nanomachines. In this paper, we approach the resource allocation problem in Molecular Nano‑networks (MCN) from the
perspective of evolutionary game theory. In particular, we consider an MCN as an organism having three types of nodes
acting as a sensor, relay, and sink, respectively. The resources are distributed among the nodes according to an evolutionary
process, which relies on the selection of the most successful organisms followed by creating their offspring iteratively. In this
regard, the success of an organism is measured by the total number of dropped messages during its life cycle. To illustrate the
evolution procedure, we design a toy problem, and then solve it analytically and using the evolution approach for comparison.
We further simulate the performance of the evolution approach on randomly generated organisms. The results reveal the
potential of evolutionary game theory tools to improve the transmission performance of MCNs.

Keywords – Evolutionary game theory, molecular communication, nano‑networks, resource allocation

1. INTRODUCTION transmitter and the optimal detection threshold of the re‑
ceiver minimizing the error probability of each hop in a
The Internet of Bio‑Nano Things (IoBNT) is a novel multi‑hop MCN are derived. In [13], the joint optimization
paradigm based on the interconnection of nanoscale de‑ of molecular resource allocation and relay location is in‑
vices and biological entities. It enables novel applica‑ vestigated to improve the error performance of a cooper‑
tions ranging from intra‑body sensing and actuator net‑ ative MC system. Similarly, in [14], the optimal molecule
works for the treatment and diagnosis of various diseases allocation among molecular receivers is determined for a
to the monitoring and control of environmental pollution cooperative MC system. In [15], information molecules
[1, 2]. Molecular Communication (MC), which is inspired with different diffusion coef icients are considered opti‑
by the natural communication between biological enti‑ mizing molecular resource allocation in molecular multi‑
ties, emerges as a promising communication technology ple access networks.
to realize nano‑networks for IoBNT applications [3], and
MC is the primary communication mode for all organisms.
recently recognized as an effective abstraction tool for un‑
derstanding several diseases [4, 5, 6]. It covers both short ranges as in synaptic communication
and long ranges as in pheromones. It is used for both fast
Research efforts in MC mainly focused on physical chan‑ acting purposes such as adrenaline and slow acting pur‑
nel modeling, modulation, coding, and detection tech‑ poses such as growth. DNA itself is an application of MC
niques [7, 8, 9, 10, 11]. Developing MC Nano‑networks that transfers information through ages. Therefore, we
(MCN) acting and communicating cooperatively to per‑ turn to evolution, the driving factor of the MC utilization
form IoBNT tasks still poses many challenges. diversity, to ind answers relating to the resource alloca‑
tion problem. One way to tap into the power of evolution
One of the most prominent challenges in MC is resource is using evolutionary game theory.
allocation. Relying on molecular dispersion instead of
electromagnetic waves, MC devices need to preserve both Game theory has been used as a tool to model networking
energy and molecules to continue their operation. As a re‑ problems and to investigate communication ef iciency of
sult, resource allocation is a more prominent problem for MCN. Game theory principles can help one explore com‑
MC compared to EM, where preserving and/or harvest‑ munication among molecular nanomachines when it is
ing energy is enough to guarantee high transmission ef i‑ hard to obtain analytical solutions because of the size of
ciency. MCN. Jiang et al [16] propose a game‑theoretic approach
for distributed research allocation for MC networks based
Realizing the importance of resource allocation in MC, on Nash equilibrium and Nash bargaining schemes. In
several works are proposed to overcome this problem. [17], evolutionary game theory tools are used to explore
In [12], the optimal number of molecules released by the the effect of transmitter behaviors, namely cooperation

© International Telecommunication Union, 2021 111