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Nov 28, 2024 - Python
omnet-simulation
Here are 26 public repositories matching this topic...
The implementation of a basic MAC protocol structure serves as a foundation for the development of more complex TDMA based link layer protocols.
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May 16, 2023 - C++
ECSNeT++ is a simulation framework built on OMNeT++ for Distributed Stream Processing applications running on Edge and Cloud computing environments.
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Jun 10, 2019 - C++
A SLAW mobility simulator based on the OMNeT++ and INET frameworks
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Feb 19, 2021 - C++
Implementation of data link layer protocols between two nodes that are connected with a noisy channel, where the transmission is not error-free, packets may get corrupted, duplicated, delayed, or lost, and the buffers are of limited sizes.
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Dec 25, 2022 - C++
A framework to offload OMNeT++ simulations to an edge computing peer-to-peer network using Go, gRPC, and UDP-Holepunching techniques
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Feb 25, 2024 - C++
OMNET++ / INET Framework - Controlled Flooding Simulation
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Mar 13, 2022 - Jupyter Notebook
OMNET++ / INET Framework - Extras for TARP Controlled Flooding Simulation
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Jan 10, 2022 - C++
MQTT-SN Protocol Implementation in OMNeT++
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May 19, 2024 - C++
Complete project is now available at https://github.com/sedgecloud
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Jan 6, 2020 - C++
My Networks Labs
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Feb 6, 2024 - C++
The Server-based Security Architecture Model (SSAM) - OMNeT++ 4.1
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Feb 4, 2022 - C++
Modeling and performance evaluation of an opportunistic cellular network. Developed using Omnetpp-6.0.1
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Jan 21, 2023 - C++
PCNSim is a payment channel network simulator that uses the OMNET++ framework. You can see more information on the official documentation: https://pcnsim.readthedocs.io/en/latest/
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Mar 16, 2023 - C++
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Apr 26, 2018 - C++
Wireless Network Simulations with OMNET++ and INET Framework
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Sep 2, 2021 - Makefile
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Oct 8, 2022 - Makefile
Thesis for my MSc in Computer Science & Engineering at Politecnico di Milano
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Apr 21, 2024
Various basic Omnet++ Concepts Implemented.
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Mar 29, 2021 - C++
This repository contains a project for detecting anomalies in network traffic using machine learning-based algorithms. The project demonstrates the application of various machine learning models to identify unusual patterns or anomalies in network traffic, which could be indicative of security threats such as intrusions or malware activity.
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Jan 9, 2025
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