8th International Conference on Body Area Networks

Research Article

dMCS: Distributed Molecular Communication Simulator

  • @INPROCEEDINGS{10.4108/icst.bodynets.2013.253576,
        author={Ali Akkaya and Tuna Tugcu},
        title={dMCS: Distributed Molecular Communication Simulator},
        proceedings={8th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2013},
        month={10},
        keywords={hla distributed simulation molecular communication},
        doi={10.4108/icst.bodynets.2013.253576}
    }
    
  • Ali Akkaya
    Tuna Tugcu
    Year: 2013
    dMCS: Distributed Molecular Communication Simulator
    BODYNETS
    ACM
    DOI: 10.4108/icst.bodynets.2013.253576
Ali Akkaya1,*, Tuna Tugcu1
  • 1: Bogazici University
*Contact email: ali.akkaya@boun.edu.tr

Abstract

Nanonetworking is a new research field in which nanotechnology and communication engineering disciplines are employed to explore the possible communication mechanisms at nanoscale. Inspired by living organisms, molecular communication is one of the alternatives that can be used for communication between nanomachines. The research activities on molecular communication depend on simulations to verify and analyze the performance of proposed models. Due to the different channel characteristics, current simulation tools can not be used as is for nanonetworking. Simulation at nanoscale requires modeling of new communication paradigm, hence either existing tools need to be extended, or new tools need to be developed. Since molecular communication involves the modeling of large number of nano-scale objects, scalability of the simulation tool is another important concern. In this paper, we introduce dMCS, a distributed molecular communication simulator design. The proposed architecture is based on High Level Architecture (HLA), which is standardized under IEEE 1516. The results show that using the proposed architecture, it is possible to exploit different scalability options to shorten the execution time significantly. This enables modeling large and complex system simulations.