skip to main content
10.1145/3625156.3625179acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicissConference Proceedingsconference-collections
research-article

Bio-inspired Nano Communication System

Published:21 November 2023Publication History

ABSTRACT

Molecular communication is an approach that draws inspiration from biological systems, involving the transmission, propagation, and reception of molecules among nanoscale machines. Achieving precise control over molecular transmissions between these nanomachines can be considered as significant obstacle in this field. Numerous research efforts have focused on modeling the communication medium, known as the channel, in molecular communication. These studies primarily adopt a communication or information-theoretical standpoint to understand and analyze the channel properties.

The primary goal of this paper is to develop a model for a time-slotted communication system among nanoscale machines within a one-dimensional environment. This communication system incorporates bio-inspired rules that are evaluated during each interval. To validate the proposed system model, different network sizes were tested using the probabilistic model checking tool PRISM.

References

  1. Sergi Abadal and Ian F Akyildiz. 2011. Automata modeling of quorum sensing for nanocommunication networks. Nano Communication Networks 2, 1 (2011), 74–83.Google ScholarGoogle ScholarCross RefCross Ref
  2. Sergi Abadal, Ignacio Llatser, Eduard Alarcón, and Albert Cabellos-Aparicio. 2012. Quorum sensing-enabled amplification for molecular nanonetworks. In Communications (ICC), 2012 IEEE International Conference on. IEEE, 6162–6166.Google ScholarGoogle ScholarCross RefCross Ref
  3. Ian F Akyildiz, Fernando Brunetti, and Cristina Blázquez. 2008. Nanonetworks: A new communication paradigm. Computer Networks 52, 12 (2008), 2260–2279.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Marwan Ammar and Otmane Ait Mohamed. 2011. Formal verification of Time-Triggered Ethernet protocol using PRISM model checker. IEEE.Google ScholarGoogle Scholar
  5. Baris Atakan and Ozgur B Akan. 2008. On channel capacity and error compensation in molecular communication. In Transactions on computational systems biology X. Springer, 59–80.Google ScholarGoogle Scholar
  6. Christel Baier and Joost-Pieter Katoen. 2008. Principles of model checking. MIT press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. David E Clapham. 1995. Calcium signaling. Cell 80, 2 (1995), 259–268.Google ScholarGoogle ScholarCross RefCross Ref
  8. Paolo Di Lorenzo, Sergio Barbarossa, and Ali H Sayed. 2013. Bio-inspired decentralized radio access based on swarming mechanisms over adaptive networks. IEEE Transactions on Signal Processing 61, 12 (2013), 3183–3197.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Falko Dressler and Ozgur B Akan. 2010. Bio-inspired networking: from theory to practice. IEEE Communications Magazine 48, 11 (2010), 2–10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Falko Dressler and Ozgur B Akan. 2010. A survey on bio-inspired networking. Computer Networks 54, 6 (2010), 881–900.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Marco Ferrari, Fardad Vakilipoor, Eric Regonesi, Mariangela Rapisarda, and Maurizio Magarini. 2022. Channel characterization of diffusion-based molecular communication with multiple fully-absorbing receivers. IEEE Transactions on Communications 70, 5 (2022), 3006–3019.Google ScholarGoogle ScholarCross RefCross Ref
  12. Jorge Torres Gómez, Ketki Pitke, Lukas Stratmann, and Falko Dressler. 2022. Age of information in molecular communication channels. Digital Signal Processing 124 (2022), 103108.Google ScholarGoogle ScholarCross RefCross Ref
  13. S Hiyama, Y Moritani, Tatsuya Suda, R Egashira, A Enomoto, M Moore, and T Nakano. 2006. Molecular communication. Journal-Institute of Electronics Information and Communication Engineers 89, 2 (2006), 162.Google ScholarGoogle Scholar
  14. Athraa Juhi Jani. 2018. Anti-Quorum Sensing Nanonetwork. Indian Journal of Public Health Research & Development 9, 12 (2018), 1108–1114.Google ScholarGoogle ScholarCross RefCross Ref
  15. Athraa Juhi Jani. 2019. Challenges and distinctions in nanonetworks design. In 2019 2nd International Conference on Engineering Technology and its Applications (IICETA). IEEE, 219–224.Google ScholarGoogle ScholarCross RefCross Ref
  16. Athraa Juhi Jani. 2019. Consensus problem with the existence of an adversary nanomachine. In New Knowledge in Information Systems and Technologies: Volume 2. Springer, 407–419.Google ScholarGoogle Scholar
  17. Athraa Juhi Jani. 2020. Pattern of diffusion recognition in a molecular communication model. In Applied Computing to Support Industry: Innovation and Technology: First International Conference, ACRIT 2019, Ramadi, Iraq, September 15–16, 2019, Revised Selected Papers 1. Springer, 349–363.Google ScholarGoogle Scholar
  18. Athraa Juhi Jani. 2023. Estimating Nodes’ Number in a Nanonetwork Using Two Algorithms. In Intelligent Sustainable Systems: Selected Papers of WorldS4 2022, Volume 1. Springer, 645–652.Google ScholarGoogle Scholar
  19. A. Juhi, D. R. Kowalski, and A. Lisitsa. 2016. Performance analysis of molecular communication model. In 2016 IEEE 16th International Conference on Nanotechnology (IEEE-NANO). 826–829. https://doi.org/10.1109/NANO.2016.7751543Google ScholarGoogle ScholarCross RefCross Ref
  20. Sergey Knyazev, Sergey Tarakanov, Vladimir Kuznetsov, Yu Porozov, Yevgeni Koucheryavy, and E Stepanov. 2014. Coarse-grained model of protein interaction for bio-inspired nano-communication. In Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2014 6th International Congress on. IEEE, 260–262.Google ScholarGoogle ScholarCross RefCross Ref
  21. Mehmet S Kuran, Huseyin Birkan Yilmaz, Tuna Tugcu, and Ian F Akyildiz. 2011. Modulation techniques for communication via diffusion in nanonetworks. In Communications (ICC), 2011 IEEE International Conference on. IEEE, 1–5.Google ScholarGoogle ScholarCross RefCross Ref
  22. Mehmet Şükrü Kuran, H Birkan Yilmaz, Tuna Tugcu, and Ian F Akyildiz. 2012. Interference effects on modulation techniques in diffusion based nanonetworks. Nano Communication Networks 3, 1 (2012), 65–73.Google ScholarGoogle ScholarCross RefCross Ref
  23. Mehmet Şükrü Kuran, H Birkan Yilmaz, Tuna Tugcu, and Bilge Özerman. 2010. Energy model for communication via diffusion in nanonetworks. Nano Communication Networks 1, 2 (2010), 86–95.Google ScholarGoogle ScholarCross RefCross Ref
  24. Marta Kwiatkowska, Gethin Norman, and David Parker. 2007. Stochastic model checking. Formal Methods for Performance Evaluation: 7th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2007, Bertinoro, Italy, May 28-June 2, 2007, Advanced Lectures 7 (2007), 220–270.Google ScholarGoogle Scholar
  25. Marta Z Kwiatkowska and Chris Thachuk. 2014. Probabilistic Model Checking for Biology.Software Systems Safety 36 (2014), 165.Google ScholarGoogle Scholar
  26. Qiang Liu and Kun Yang. 2015. Channel capacity analysis of a diffusion-based molecular communication system with ligand receptors. International Journal of Communication Systems 28, 8 (2015), 1508–1520.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Tadashi Nakano, Yutaka Okaie, and Jian-Qin Liu. 2012. Channel model and capacity analysis of molecular communication with Brownian motion. IEEE communications letters 16, 6 (2012), 797–800.Google ScholarGoogle ScholarCross RefCross Ref
  28. Hoda ShahMohammadian, Geoffrey G Messier, and Sebastian Magierowski. 2012. Optimum receiver for molecule shift keying modulation in diffusion-based molecular communication channels. Nano Communication Networks 3, 3 (2012), 183–195.Google ScholarGoogle ScholarCross RefCross Ref
  29. Gokberk Yaylali, Bayram Cevdet Akdeniz, Tuna Tugcu, and Ali Emre Pusane. 2023. Channel modeling for multi-receiver molecular communication systems. IEEE Transactions on Communications (2023).Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Bio-inspired Nano Communication System
            Index terms have been assigned to the content through auto-classification.

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in
            • Published in

              cover image ACM Other conferences
              ICISS '23: Proceedings of the 2023 6th International Conference on Information Science and Systems
              August 2023
              301 pages
              ISBN:9798400708206
              DOI:10.1145/3625156

              Copyright © 2023 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 21 November 2023

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • research-article
              • Research
              • Refereed limited
            • Article Metrics

              • Downloads (Last 12 months)10
              • Downloads (Last 6 weeks)3

              Other Metrics

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader

            HTML Format

            View this article in HTML Format .

            View HTML Format