Ns-3 Simulator
Ns-3 Simulator - Related Videos
12:39
Computational Fluid Dynamics Simulations of Blood Flow in a Cerebral Aneurysm
0 Views •
2023
Source: Joseph C. Muskat, Vitaliy L. Rayz, and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana The objective of this video is to describe recent advancements of computational fluid dynamic (CFD) simulations based on patient- or animal-specific vasculature. Here, subject-based vessel segmentations were created, and, using a combination of open-source and commercial tools, a high-resolution numerical solution was determined within a flow model.
03:22
Evaluating Intestinal Bacterial Colonization in Germ-Free C. elegans
0 Views •
2025
Source: Taylor, M. N., et.al. Using Single-Worm Data to Quantify Heterogeneity in Caenorhabditis elegans-Bacterial Interactions. J. Vis. Exp. (2022)This video demonstrates the exposure of germ-free, age-matched Caenorhabditis elegans worms to a bacterial strain for intestinal colonization. It explains the selective removal of non-adhered and external bacteria, leaving only viable bacteria adhered to the gut epithelium for quantification.
09:46
MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
0 Views •
Cited by 48 •
2012
An efficient way to gain insight into how humans navigate themselves in three dimensions is described. The method takes advantage of a motion simulator capable of moving observers in ways unattainable by traditional simulators. Results confirm that movement in the horizontal plane is underestimated, while vertical movement is overestimated.
02:54
Exposing a Synthetic Oral Bacterial Community to Simulated Phases of Digestion
0 Views •
2025
Source: Arroyo, M. C., et al. Assessing the Viability of a Synthetic Bacterial Consortium on the In Vitro Gut Host-microbe Interface. J. Vis. Exp. (2018)This video demonstrates the viability assessment of a synthetic oral microbial community during simulated oral, gastric, and intestinal digestion. Bacterial survival is quantified after each phase, revealing a progressive decline due to digestive stress.
11:29
Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
0 Views •
Cited by 15 •
2014
A new computational system featuring GPU-accelerated molecular dynamics simulation and 3D/VR visualization, analysis and manipulation of nanostructures has been implemented, representing a novel approach to advance materials research and promote innovative investigation and alternative methods to learn about material structures with dimensions invisible to the human eye.
FAQs
The key mechanism is scheduled-event processing: simulated time moves from one event to the next rather than following wall-clock time. Events can represent packet transmission, reception, propagation delay, or routing decisions. This lets an experiment expose how timing and protocol actions interact under a chosen network scenario.
Software objects provide the model’s adjustable structure. Nodes represent network participants, while links, channels, applications, and protocol stacks describe connectivity, communication behavior, and protocol operation. Changing these components allows an engineer to construct alternative wired, wireless, or Internet-based scenarios without rebuilding a physical testbed for each comparison.
Packet-level traces preserve detailed evidence about what occurs during a run, while aggregate metrics summarize performance. Throughput, latency, reliability, and congestion measurements can therefore be examined together, helping researchers connect individual communication events with overall network behavior and compare competing designs under controlled conditions systematically.
A typical study begins by specifying nodes, links or channels, applications, and protocol stacks, then configuring the network scenario and the events to observe. The run produces packet-level traces and performance measurements. Researchers can repeat this process across alternative designs, keeping conditions controlled for meaningful comparison.
The model can support evaluations of communication protocols, network architectures, and distributed systems before deployment. Engineers may examine whether a design sustains throughput, limits latency, maintains reliability, or manages congestion in wired, wireless, or Internet-based settings. These results help narrow design choices before physical testing.
It offers a reproducible way to study network behavior while reducing the cost and complexity of physical experiments. Students and researchers can change modeled components, run controlled scenarios, inspect traces, and compare performance outcomes. This combination supports learning about protocol operation as well as systematic evaluation of emerging network technologies.