Search Results for "command-line"
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Showing 5 open source projects for "command-line"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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GatcomSUMO
Automates the building of VANET simulations using SUMO and OMNeT++
...The tasks related to the generation of abstract or synthetic scenarios, the download and conversion of network scenarios based on real maps (e.g. from OpenStreetMap), the route creation process, and the vehicles mobility modelling are integrated in a user-friendly graphical interface. This tool performs the necessary actions by invoking the set of utilities included in SUMO, saving the user from typing complex command-line orders. GatcomSUMO visualizes the network and routes easily, and they are created in such a way to meet the requirements of the involved simulators, in particular OMNeT++, in order to avoid misunderstandings and runtime errors. The application allows the conversion of the spatial coordinates used by SUMO into those used by OMNeT++, which is essential to place fixed elements like RSUs. -
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UM-OLSR is an OLSR (Optimized Link State Routing protocol) implementation for the ns2 network simulator.
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This project is based on a personal effort for researches on dynamics of coevovling networks. As a physicist, I am trying to build a framework for discrete-time dynamics of general networks, and its software libraries with APIs.
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Yans is a extensible, mixed-level, Monte-Carlo Method based, discrete event network simulator. Yans is divided into interacting layers, namely: core, topology, nodes, monitors; and is driven by a config-file that describes the setup of the network.
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Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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NS-2 Trace Statistics is a tool for easy generation of summary statistics from Network Simulator trace files, such as: total and network delay, packets generated, sent, received and dropped, run length histograms and MRU stack depth.
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