NDLI: Using a genetic-based algorithm to solve the scheduling optimization problem for long-range molecular communications in nanonetworks

Content Provider	IEEE Xplore Digital Library
Author	Ghasempour, A.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA (Ghasempour, A.)
Abstract	Inspired by nature, nanonetworks can expand the capabilities of nanomachines with regards to execution of more complex tasks, extension of workspace and coverage. Various communication techniques such as acoustic, nanomechanical, electromagnetic and molecular communications are proposed for nanonetworks but molecular communication is the most promising method. Molecular communication has three categories in terms of distance between nanomachines: short range, medium range, and long range. In this paper, axon-based molecular communication as one of wired long range molecular communication options in nanonetwork is studied. Since axon-based molecular communication uses neural network (body area network (BAN)) as an underlying structure to connect nanomachines, neuron and neural network are described. This paper uses a neural time division multiple access (NTDMA) scheduling to allow nanomachines to send their information through a shared neural network to the destination nanomachine (sink) without any collision and interference. In a NTDMA protocol, nanomachines activate neurons, one after the other, in their own time slots. Since determination of these time slots is a multi-objective optimization problem, thus a genetic-based algorithm (GBA) is proposed to solve it. Simulation results verify that GBA obtains the best feasible solutions and outperforms some existing methods.
Starting Page	1825
Ending Page	1829
File Size	1048179
Page Count	5
File Format	PDF
e-ISBN	9781467367820
DOI	10.1109/PIMRC.2015.7343595
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nanobioscience Biological cells Molecular communication Biological neural networks Scheduling TDMA scheduling Evolutionary Methods Genetic Algorithm Molecular Communication Nanonetwork Neural Network Optimization methods
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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