A Computational Multiagent Model of Bioluminescent Bacteria for the Emergence of Self-Sustainable and Self-Maintaining Artificial Wireless Networks

Authors

  • Nedjma Djezzar University of Biskra, LESIA laboratory University of Toulouse, IRIT - CNRS - UMR5505
  • Iñaki Fernández Pérez University of Toulouse, IRIT - CNRS - UMR5505
  • NourEddine Djedi University of Biskra, LESIA laboratory
  • Yves Duthen University of Toulouse, IRIT - CNRS - UMR5505

DOI:

https://doi.org/10.31449/inf.v43i3.2381

Abstract

Biology is a rich source of inspiration in designing digital artifacts capable of autonomous, cooperative and distributed behaviors. Particularly, conceptual links can be established between (1) communication networks and (2) colonies of bacteria that communicate using chemical molecules. The goal of this paper is to propose a computational multiagent model of an interspecies bacterial communication system, termed quorum sensing, and analyze its self-sustainability and its self-maintaining ability to cooperatively form artificial wireless networks. Specifically, we propose a bottom-up agent-based approach combined with Ordinary Differential Equations, which abstract the intracellular dynamics, such as a proposed metabolism model that serves as a basis underlying self-sustainable networks. Results show that artificial bacterial cells have regeneration abilities in the light of random cell death and selected area for cell death, and a metabolism allowing them to exploit their own produced energy to cooperate at the population level to exhibit near-optimal self-organizing light-producing behaviors. The resulting artificial networks display several beneficial properties and could be used for the emergence of resistant wireless network topologies without the use of overhead messages.

Author Biographies

Nedjma Djezzar, University of Biskra, LESIA laboratory University of Toulouse, IRIT - CNRS - UMR5505

Nedjma Djezzar was born in Constantine (Algeria) in 1984. She obtained an engineer's degree in computer science (advanced information systems specialty) with honors from Mentouri University (Constantine, Algeria) in 2007, and a Magister degree in computer science (image synthesis and artificial life specialty) with high honors from Biskra University (Biskra, Algeria) in 2010.Between 2009 and 2011, she was a Teaching Assistant responsible of the computer science module at the department of Languages and translation of the University of Constantine. She is currently an assistant professor at the department of Computer Science of Batna University (Algeria). She is also a Ph.D. student at University of Toulouse Capitole  (France) and University of Biskra (Algeria). She has published her work in top-tier venues in the field of Artificial Life. Her interests cover Artificial Life, Bioinspired Computation, Morphogenetic Engineering, Self-Organizing Networks. 

Iñaki Fernández Pérez, University of Toulouse, IRIT - CNRS - UMR5505

Iñaki Fernández Pérez was born in Madrid (Spain) in 1988. He obtained a B.Sc. in computer science (systems specialty) with honors from the Universidad de Valladolid (Valladolid, Spain) in 2011, and a M.Sc. in computer science (artificial intelligence specialty) from the Université de Lorraine (Nancy, France) in 2013, and a Ph.D. in evolutionary swarm robotics from the Université de Lorraine (Nancy, France)  in 2017.Between 2010 and 2017, he occupied a Software Engineer position in Semantic Web for the French national institute for research in computer science (INRIA), as well as a Teaching Assistant (DCCE), and a Teaching and Research Fellow (ATER) at Univesité de Lorraine. He is currently a Postdoctoral Fellow at ReVa team in IRIT lab in Toulouse (France). He has published his work in top-tier venues in the field of swarm robotics  and Evolutionary Computation. His interests cover Evolutionary Swarm Robotics, Artificial Life, Bioinspired Computation and Machine Learning.Since 2017, Dr. Fernández Pérez is the vice-chair of the Student/Postdoc group at the International Society for Artificial Life. He is an active member of the ALife and Evolutionary Computation community, refereeing for several conferences and journals in these fields, as well as collaborating in the organization of conference and other scientific events.

NourEddine Djedi, University of Biskra, LESIA laboratory

NourEddine Djedi was born in Biskra (Algeria) in 1963. He obtained a B.Sc. in computer science (systems specialty) with honors from the USTHB (Algiers, Algeria) in 1986, and a M.Sc. in computer science (Computer Graphics specialty) from the Université Paul Sabatier (Toulouse, France) in 1987, and a Ph.D. in Declarative modeling from the Université Paul Sabatier (Toulouse, France) in1991.Between 1988 and 1990, he occupied a Teaching and Research Fellow (ATER) at Université Paul Sabatier while being a member of the "Computer Graphics" team at the IRIT laboratory in Toulouse. He teaches computer science at Biskra university since 1992 and currently holds the position of professor.He has published about 90 refereed journal and conference papers. His research interests include robotics, image synthesis, artificial life and behavioral animation.He held the position of Deputy Director of Research and the position of President of the University of Biskra from 1994 to 2000, as well as the position of Information Technology Advisor in the Presidency of the Republic of Algeria between 2001 and 2004. In addition, he held the position of director of the LESIA laboratory (Biskra University) between 2007 and 2011.

Yves Duthen, University of Toulouse, IRIT - CNRS - UMR5505

Prof. Dr. Yves Duthen is a Research Professor of Artificial Life and Virtual Reality at IRIT lab, University of Toulouse 1-Capitole (France). He received his Ph.D. degree from the University Paul Sabatier in 1983 and the “French Habilitation” degree in 1993 to become full Professor. He has worked in image synthesis during the 1980’s and focused on Behavioral Simulation based on evolutionary mechanism since 1990. He has published
 about 130-refereed journal and conference papers and has directed 15 PhD theses. He has pioneered research in artificial life for building adaptive artificial creatures and focuses now on embedded metabolism and morphogenetic engineering.

References

T. E. Gorochowski, “Agent-based modelling in synthetic biology,” Essays Biochem., vol. 60, no. 4, pp. 325–336, 2016.

B. L. Bassler, “How bacterial talk to each other: regulation of gene expression by quorum sensing,” Curr. Opin. Microbiol., vol. 2, no. 6, pp. 582–587, 1999.

K. O. Stanley and R. Miikkulainen, “A Taxonomy for Artificial Embryogeny,” Artif. Life, vol. 9, no. 2, pp. 93–130, 2003.

R. Doursat, H. Sayama, and O. Michel, “A review of morphogenetic engineering,” Nat. Comput., vol. 12, no. 4, pp. 517–535, 2013.

A. Chavoya and Y. Duthen, “A cell pattern generation model based on an extended artificial regulatory network,” Biosystems, vol. 94, no. 1–2, pp. 95–101, 2008.

S. Nichele, T. E. Glover, and G. Tufte, “Genotype Regulation by Self-modifying Instruction-Based Development on Cellular Automata,” Springer, Cham, 2016, pp. 14–25.

S. Majumdar and S. Mondal, “Conversation game: talking bacteria,” J. Cell Commun. Signal., vol. 10, no. 4, pp. 331–335, 2016.

F. Dressler and O. B. Akan, “A survey on bio-inspired networking,” Comput. Networks, vol. 54, no. 6, pp. 881–900, 2010.

N. Ouannes, N. Djedi, Y. Duthen, and H. Luga, “Emergent group behaviors from bacteria quorum sensing simulation,” in 21st AROB, 2016, pp. 62–67.

F. J. Romero-Campero and M. J. Pérez-Jiménez, “A Model of the Quorum Sensing System in Vibrio fischeri Using P Systems,” Artif. Life, vol. 14, no. 1, pp. 95–109, 2008.

B. E. Beckmann and P. K. Mckinley, “Evolving Quorum Sensing in Digital Organisms,” in GECCO’09 Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009, pp. 97–104.

P. Bechon and J.-J. Slotine, “Synchronization and quorum sensing in a swarm of humanoid robots,” arXiv Prepr. arXiv1205.2952, 2012.

W. Ji et al., “A Formalized Design Process for Bacterial Consortia That Perform Logic Computing,” PLoS One, vol. 8, no. 2, p. e57482, 2013.

Feng Tan and J.-J. Slotine, “A quorum sensing inspired algorithm for dynamic clustering,” in 52nd IEEE Conference on Decision and Control, 2013, pp. 5364–5370.

H. Shum and A. C. Balazs, “Synthetic quorum sensing in model microcapsule colonies,” Proc. Natl. Acad. Sci., vol. 114, no. 32, pp. 8475–8480, 2017.

B. Niu, H. Wang, Q. Duan, and L. Li, “Biomimicry of quorum sensing using bacterial lifecycle model,” BMC Bioinformatics, vol. 14, no. Suppl 8, p. S8, 2013.

D. A. Sofge and W. F. Lawless, “Quorum Sensing for Collective Action and Decision-Making in Mobile Autonomous Teams,” in ICAART (1), 2011, pp. 195–204.

A. C. Burgos and D. Polani, “Cooperation and antagonism in information exchange in a growth scenario with two species,” J. Theor. Biol., vol. 399, pp. 117–133, 2016.

J. W. Williams, X. Cui, A. Levchenko, and A. M. Stevens, “Robust and sensitive control of a quorum-sensing circuit by two interlocked feedback loops,” Mol. Syst. Biol., vol. 4, no. 1, p. 234, 2008.

P. Melke, P. Sahlin, A. Levchenko, and H. Jönsson, “A cell-based model for quorum sensing in heterogeneous bacterial colonies,” PLoS Comput. Biol., vol. 6, no. 6, p. e1000819, 2010.

G. Wei, C. Walsh, I. Cazan, and R. Marculescu, “Molecular tweeting: Unveiling the social network behind heterogeneous bacteria ions,” in BCB 2015 - 6th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 2015, pp. 366–375.

A. A. Aziz, Y. A. Sekercioglu, P. Fitzpatrick, and M. Ivanovich, “A Survey on Distributed Topology Control Techniques for Extending the Lifetime of Battery Powered Wireless Sensor Networks,” IEEE Commun. Surv. Tutorials, vol. 15, no. 1, pp. 121–144, 2013.

J. F. Miller, “Evolving Developmental Programs for Adaptation, Morphogenesis, and Self-Repair,” in European Conference on Artificial Life., 2004, pp. 256–265.

J. F. Miller, “Evolving a Self-Repairing, Self-Regulating, French Flag Organism,” in Genetic and Evolutionary Computation Conference, 2004, pp. 129–139.

H. Liu, J. F. Miller, and A. M. Tyrrell, “An intrinsic robust transient fault-tolerant developmental model for digital systems,” in Workshop on Regeneration and Learning in Developmental Systems, Genetic and Evolutionary Computation Conference., 2004.

K. Fleischer, “Investigations with a Multicellular Developmental Model,” in C. G. Langton & T. Shimohara (Eds.), Artificial Life V, 1996, pp. 229–236.

S. Cussat-Blanc, H. Luga, and Y. Duthen, “Cell2Organ: Self-repairing artificial creatures thanks to a healthy metabolism,” in 2009 IEEE Congress on Evolutionary Computation, CEC 2009, 2009, pp. 2708–2715.

N. Djezzar, N. Djedi, S. Cussat-Blanc, H. Luga, and Y. Duthen, “L-systems and artificial chemistry to develop digital organisms,” in 2011 IEEE Symposium on Artificial Life (ALIFE), 2011, pp. 225–232.

G. Ferreira, M. Smiley, M. Scheutz, and M. Levin, “Dynamic Structure Discovery and Repair for 3D Cell Assemblages,” in Proceedings of the Artificial Life Conference 2016, 2016, pp. 352–359.

L. Cobo, A. Quintero, and S. Pierre, “Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics,” Comput. Networks, vol. 54, no. 17, pp. 2991–3010, 2010.

A. Giagkos and M. S. Wilson, “Swarm intelligence to wireless ad hoc networks: adaptive honeybee foraging during communication sessions,” Adapt. Behav., vol. 21, no. 6, pp. 501–515, 2013.

I. Bojic, V. Podobnik, I. Ljubi, G. Jezic, and M. Kusek, “A self-optimizing mobile network: Auto-tuning the network with firefly-synchronized agents,” Inf. Sci. (Ny)., vol. 182, no. 1, pp. 77–92, 2012.

Z. G. Al-Mekhlafi, Z. M. Hanapi, M. Othman, and Z. A. Zukarnain, “A firefly-inspired scheme for energy-efficient transmission scheduling using a self-organizing method in a wireless sensor networks,” J. Comput. Sci., vol. 12, no. 10, pp. 482–494, 2016.

N. El Houda Bahloul, S. Boudjit, M. Abdennebi, and D. E. Boubiche, “A Flocking-Based on Demand Routing Protocol for Unmanned Aerial Vehicles,” J. Comput. Sci. Technol., vol. 33, no. 2, pp. 263–276, 2018.

J. Monod, “The Growth of Bacterial Cultures,” Annu. Rev. Microbiol., vol. 3, no. 1, pp. 371–394, 1949.

A. H. Stouthamer and C. Bettenhaussen, “Utilization of energy for growth and maintenance in continuous and batch cultures of microorganisms. A reevaluation of the method for the determination of ATP production by measuring molar growth yields,” BBA Reviews On Bioenergetics, vol. 301, no. 1. pp. 53–70, 1973.

S. A. L. M. Kooijman, Dynamic energy budget theory for metabolic organisation. Cambridge University Press, 2010.

A. I. Psarras and I. G. Karafyllidis, “Simulation of the Dynamics of Bacterial Quorum Sensing,” IEEE Trans. Nanobioscience, vol. 14, no. 4, pp. 440–446, Jun. 2015.

D. J. Sexton and M. Schuster, “Nutrient limitation determines the fitness of cheaters in bacterial siderophore cooperation,” Nat. Commun., vol. 8, no. 1, p. 230, 2017.

C. Moreno-Fenoll, M. Cavaliere, E. Martínez-García, and J. F. Poyatos, “Eco-evolutionary feedbacks can rescue cooperation in microbial populations,” Sci. Rep., vol. 7, p. 42561, 2017.

S. S. Jang, K. T. Oishi, R. G. Egbert, and E. Klavins, “Specification and Simulation of Synthetic Multicelled Behaviors,” ACS Synth. Biol., vol. 1, no. 8, pp. 365–374, 2012.

C. Anetzberger, T. Pirch, and K. Jung, “Heterogeneity in quorum sensing-regulated bioluminescence of Vibrio harveyi,” Mol. Microbiol., vol. 73, no. 2, pp. 267–277, 2009.

N. Ouannes, N. Djedi, H. Luga, and Y. Duthen, “Modeling a bacterial ecosystem through chemotaxis simulation of a single cell,” Artif. Life Robot., vol. 19, no. 4, pp. 382–387, 2014.

S. Forrest and T. Jones, “Modeling Complex Adaptive Systems with Echo,” in Complex Systems: Mechanisms of Adaptation, 1993, pp. 3–21.

S. Y. Queck et al., “RNAIII-independent target gene control by the agr quorum- sensing system: insight into the evolution of virulence regulation in Staphylococcus aureus,” Mol. Cell, vol. 32, no. 1, pp. 150–158, 2008.

Y.-C. Yong and J.-J. Zhong, “Impacts of Quorum Sensing on Microbial Metabolism and Human Health,” in Advances in biochemical engineering/biotechnology, vol. 131, 2012, pp. 25–61.

E. Goo, J. H. An, Y. Kang, and I. Hwang, “Control of bacterial metabolism by quorum sensing,” Trends in Microbiology, vol. 23, no. 9. 2015.

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Published

2019-09-30

How to Cite

Djezzar, N., Fernández Pérez, I., Djedi, N., & Duthen, Y. (2019). A Computational Multiagent Model of Bioluminescent Bacteria for the Emergence of Self-Sustainable and Self-Maintaining Artificial Wireless Networks. Informatica, 43(3). https://doi.org/10.31449/inf.v43i3.2381

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Regular papers