Akademik Veri Yönetim Sistemi
NANO COMMUNICATION NETWORKS, cilt.5, sa.4, ss.83-96, 2014 (SCI-Expanded)
Recent studies in nanotechnology show that the membrane selection process and distance adaptation algorithms can be used to maintain the simultaneous molecular communication in multi-user nanonetworks. However, such methods prevent the cooperation between different nanodevices, thus, degrade the performance. Moreover, the existing frameworks are not suitable for dense nanonetworks containing huge number of nano-devices. To the best of our knowledge, a simultaneous communication framework that enables cooperation has not been covered based on the challenges caused by the diffusion nature of the Concentration Shift Keying (CSK)-based molecular communication. First of all, the transmission of the molecular signal through all available channels is one of the most important challenge as it increases the interference between devices. Moreover, the experienced latency and attenuation of the chemical signal complicate the decoding process at the receiver side and necessitate a more complex nanomachine model. Additionally, synchronization between nanodevices becomes problematic. Having these challenges in mind, we propose an interference-free, simultaneous and selective communication model for Flow-Based Architecture (FBA)-based Nanonetwork. The proposed framework uses a molecule blocking filter structure that enables inter-group synchronization and limits the side effects of the diffusion nature. The packet-based communication is used in the proposed framework, and we defined a complete packet architecture that consists of synchronization bits, the address of the receiver and the data. The filters transmission control mechanism is also presented as a Markov chain-based active flow control structure. The performance of the proposed framework is evaluated from both user perspective and network perspective. We observed that the proposed framework can support up to 8 simultaneous selective molecular communications in a 10-user nanonetwork. (C) 2014 Elsevier Ltd. All rights reserved.