Lightweight, self-tuning data dissemination for dense nanonetworks

A nanonetwork comprises a high number of autonomous nodes with wireless connectivity, assembled at micro-to-nanoscale. In general, manufacturing and cost considerations imply that nanonetworking approaches should have minimal complexity, ideally without sacrifices in network coverage. The present paper studies a networking approach fit for static, dense topologies comprising numerous, identical, computationally-constrained nodes. These attributes are especially important in the context of recently proposed applications of nanonetworks. The presented networking approach assumes that each node is equipped with 10 bits of reclaimable storage to accommodate four integer counters, and a trivial set of integer operations on them. These modest resources are used for logging packet reception statistics. Nanonodes with good reception serve as retransmitters within the network. This classification process is based on the Misra–Gries algorithm, used for detecting frequent items into sequential streams. Evaluation via extensive simulations in various 2D and 3D topologies yields high network coverage, achieved with less resources than related approaches.