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Dynamic routing and congestion control are two major problems in software-defined hybrid satellite-terrestrial multicast networks research. Due to terrestrial users being allowed to join or leave the multicast group at any time and the differences between the satellite and the terrestrial networks, many multicast routing algorithms reroute rapidly and thus increase the rerouting overheads. Meanwhile, the congestion ratio is increased by some hot nodes of satellite-terrestrial link transmission paths. This paper focuses on rerouting overheads and congestion problems in satellite-terrestrial multicast networks. We present a satellite-terrestrial network architecture with the Software-Defined Networking (SDN) features to offer dynamic multicast services for terrestrial users. A Two-Layered Shared Tree Multicast (TSTM) routing algorithm is proposed to achieve efficient dynamic multicast group management, address the trade-off between bandwidth consumption and rerouting overheads. The algorithm also implements congestion control by using a load factor to reflect on the global network bandwidth usage in routing calculations. This algorithm balances the rerouting frequencies of satellite and terrestrial networks to decrease the rerouting overheads and also reduces the network congestion ratio. The simulation shows TSTM decreases rerouting cost, user time delay, and node congestion ratio compared with the locality-aware multicast approach (LAMA).

Self-assembly formation of nanoparticles (NPs) is a central theme in nanotechnology that has garnered significant attention in both academia and industry. The size of self-assembled NPs plays crucial role in their physicochemical properties. It has long been known that when macromolecules in a solvent being exposed to an anti-solvent, they can spontaneously form NPs of varying sizes through static diffusion (mixing rate = 0) and dynamic convection (mixing rate > 0). However, the impact of solvent mixing rate on the size of self-assembled NPs remains a mystery. Here, for the first time, we mathematically and experimentally prove that Reynolds number (Re), which quantifies fluid turbulence, is decisive on the self-assembly formation of NPs, by exponentially influencing the way kinetic energy of precursor molecules converting into surface energy of subsequent NPs. We surprisingly find that various self-assembly systems share a very similar critical value of Re about 1,000 ~ 1,200, which predetermines whether self-assembly occurs following a low or high energy dissipation pathway. This new framework further enables us to quantitatively determine energy conversion efficiency of a self-assembly process, measure surface tension of NP in a complex system, and predict NP size at arbitrary Re (including 0), which cannot be achieved in the past due to the limits of technology.