Abstract
Molecular communication provides communication and networking capabilities for nanomachines such as biosensors and bio-actuators to form and enable Body Area NanoNetworks (BANNs). This paper considers neuron-based molecular communication, which utilizes natural neurons as a primary component to build BANNs, and proposes an end-to-end software architecture to manage and control neuron-based BANNs through a series of software services. Those services aid to realize end user applications in healthcare, such as biomedical and rehabilitation applications. In the proposed architecture, a neuron-based BANN consists of a set of nanomachines and a network of neurons that are artificially formed into a particular topology. This paper investigates two mechanisms in the proposed architecture: (1) an artificial assembly method to form neurons into specific three-dimensional topology patterns and (2) a communication protocol for neuronal signaling based on Time Division Multiple Access (TDMA), called Neuronal TDMA. The assembly method uses silica beads as growth surface and bead-bead contacts as geometrical constraints on neuronal connectivity. A web lab experiment verifies this method with neuronal hippocampal cells. Neuronal TDMA leverages an evolutionary multiobjective optimization algorithm (EMOA) to optimize the signaling schedules for nanomachines. Simulation results demonstrate that the Neuronal TDMA efficiently obtains quality solutions.
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Atakan B, Balasubramaniam S, Akan OB (2012) Body area nanonetworks with molecular communications in nanomedicine. IEEE Commun Mag 50(1):28–34
Balasubramaniam S, Boyle NT, Della-Chiesa A, Walsh F, Mardinoglu A, Botvich D, Prina-Mello A (2011) Development of artificial neuronal networks for molecular communication. Nano Commun Netw 2(2–3):150–160
Deb K, Agrawal S, Pratab A, Meyarivan T (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Proceedings Int’l conference on parallel problem solving from nature
Freitas RA (2005) Current status of nanomedicine and medical nanorobotics. J Comput Theor Nanosci 2(1):1–25
Gine LP, Akyildiz IF (2009) Molecular communication options for long range nanonetworks. Comput Netw 53:2753–2766
Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison Wesley
Hosokawa C, Sakamoto Y, Kudoh SN, Hosokawa Y, Taguchi T (2013) Femtosecond laser-induced stimulation of a single neuron in a neuronal network. Appl Phys A 110(3):607–612
Ishibuchi H, Tsukamoto N, Hitotsuyanagi Y, Nojima Y (2008) Effectiveness of scalability improvement attempts on the performance of NSGA-II for many-objective problems. In: Proceedings ACM conference on genetic and Evolution Computation
Jun SB, Hynd MR, Dowell-Mesfin N, Smith KL, Turner JN, Shain W, Kima SJ (2007) Low-density neuronal networks cultured using patterned polyl-L-lysine on microelectrode arrays. J Neurosci Methods 160(2):317–326
Lio P, Balasubramaniam S (2012) Opportunistic routing through conjugation in bacteria communication nanonetwork. Nano Comm Networks 3(1)
Luczak A (2010) Measuring neuronal branching patterns using model-based approach. Front Comput Neurosci 4:135
Moo Sung Chae MRYLHWL, Yang Z (2009) A 128-channel 6mw wireless neural recording ic with spike feature extraction and uwb transmitter. IEEE Trans Neur Sys Reh 17(4):312–321
Moore M, Enomoto A, Nakano T, Egashira R, Suda T, Kayasuga A, Kojima H, Sakakibara H, Oiwa K (2006) A design of a molecular communication system for nanomachines using molecular motors. In: Proceedings IEEE Int’l Conference on Pervasive Computing and Communications Workshops
Nakano T, Moore M, Wei F, Vasilakos AV, Shuai JW (2012) Molecular communication and networking: opportunities and challenges. IEEE Trans Nanobiosci 11(2):135–148
Nakano T, Suda T, Moore M, Egashira R, Enomoto A, Arima K (2005) Molecular communication for nanomachines using intercellular calcium signaling. In: Proceedings IEEE Int’l Conferences on Nanotechnology
Partridge K, Dahlquist B, Veiseh A, Cain A, Foreman A, Goldberg J, Borriello G (2001) Empirical measurements of intrabody communication performance under varied physical configurations. Proc User Interface Softw Technol Symp
Silvestro Micera KY, Navarro X (2009) Interfacing with the peripheral nervous system to develop innovative neuroprostheses. IEEE Trans Neur Sys Reh 17(5):417–418
Stuart G, Schiller J, Sakmann B (1997) Action potential initiation and propagation in rat neocortical pyramidal neurons. J Physiol 505:3
Suda T, Moore M, Nakano T, Egashira R, Enomoto A (2005) Exploratory research on molecular communication between nanomachines. Proc ACM Genetic Evol Computat Conference
Tezcan H, Oktug S, Kok FN (2012) Neural delay lines for tdma based molecular communication in neural networks. Proc. IEEE Int’l Conference on Communications
Zimmerman T (1996) Personal area networks (PAN): Near-field intra-body communication. IBM Syst J 35(3–4):609–617
Zitzler E, Laumanns M, Thiele L (2002) SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization. In: Evol. Methods for Design, Optimisation and Control with Application to Industrial Problems
Zitzler E, Thiele L (1998) Multiobjective optization using evolutionary algorithms: A comparative study. In: Proc. Int’l Conf. on Parallel Problem Solving from Nature
Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans Evol Computat 3 (4)
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This work is supported in part by the FiDiPro programme of Academy of Finland “Nanocommunication Networks” 2012–2016.
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Suzuki, J., Balasubramaniam, S., Pautot, S. et al. A Service-Oriented Architecture for Body Area NanoNetworks with Neuron-based Molecular Communication. Mobile Netw Appl 19, 707–717 (2014). https://doi.org/10.1007/s11036-014-0549-0
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DOI: https://doi.org/10.1007/s11036-014-0549-0