NS-2 is a discrete event network simulator for modelling network protocols and traffic. It models packets, links, queues and supports protocols like TCP and IP. NS-2 allows simulation of different network scenarios and is widely used for networking research. Simulations are created using OTcl scripts which interface with the C++-based simulator core. The document provides an overview of NS-2 architecture, usage and programming and includes an example simulation script.
The document provides an overview of the Network Simulator 2 (NS2). It discusses that NS2 is a discrete event simulator targeted at networking research and education. It allows modeling of both wired and wireless networks. The backend is written in C++ and the frontend is written in OTcl. The document outlines how to download, install, and use NS2 to create network topologies, configure protocols, generate traffic, insert errors, run simulations, and analyze trace files.
This document provides an overview and tutorial on using the ns-2 network simulator. It covers the basics of ns-2 including its architecture, using OTcl and C++, event-driven simulation, tracing packets, creating network topologies, inserting errors, setting up routing, creating connections using TCP and applications, and visualizing simulations using Nam. The tutorial aims to help users understand the basic concepts of ns-2, set up their own network topologies and simulations, add traffic, run simulations, and use visualization tools.
Presentation by Mr. Vibin Chander, CEO, Shabari Software Solutions, CBE during the Faculty development Programm on NS2 organized by Department of Computer Science, Rathinam College of Arts and Computer Science (Autonomous), Eachanari, Coimbatore - 641021.
This document provides an introduction and overview of NS2 (Network Simulator 2). It discusses that NS2 is an open-source discrete event network simulator used to simulate TCP/IP networks. It describes the architecture of NS2 which uses C++ for internal operations and OTCL as the user interface. It also discusses the advantages of using Linux over Windows for NS2 and provides some basic Linux commands.
NS-2 is a discrete event network simulator used to model computer networks. It includes implementations of many common network protocols like TCP and various routing protocols. NS-2 uses C++ for core functionality and OTcl as a front-end for configuration and scripting. It models networks as nodes connected by links, with agents running protocols at each node. Users write OTcl scripts to define network topologies and scenarios that are then simulated to produce trace files for analysis.
This document provides an overview of network simulation using the Network Simulator 2 (NS2). It discusses the motivation for network simulation, what simulation is, and the advantages and drawbacks of simulation. It then describes the structure and programming of a simulation, including maintaining event lists and processing events. The document outlines NS2, including how to get it, create topologies, add traffic, observe behavior using NAM, and provides examples of simple NS2 scripts. It also briefly discusses adding new protocols to NS2 and finding documentation. The key points covered are the fundamentals and use of discrete event network simulation using the NS2 tool.
NS2 - the network simulator which is proved useful in studying the dynamic nature of communication networks. Simulation of wired as well as wireless network functions and protocols( e.g. routing algorithms, TCP, UDP ) can be done using NS2
Ns is an object-oriented network simulator written in C++ and OTcl that is used to simulate wired and wireless networks. It allows debugging of network protocols and configurations efficiently without physical equipment. Ns simulates network components, traffic models, transport and routing protocols, and physical media. It consists of an event scheduler that handles the simulation by processing events in chronological order.
The document provides an overview of the Network Simulator 2 (NS2). It discusses that NS2 is a discrete event simulator targeted at networking research and education. It allows modeling of both wired and wireless networks. The backend is written in C++ and the frontend is written in OTcl. The document outlines how to download, install, and use NS2 to create network topologies, configure protocols, generate traffic, insert errors, run simulations, and analyze trace files.
This document provides an overview and tutorial on using the ns-2 network simulator. It covers the basics of ns-2 including its architecture, using OTcl and C++, event-driven simulation, tracing packets, creating network topologies, inserting errors, setting up routing, creating connections using TCP and applications, and visualizing simulations using Nam. The tutorial aims to help users understand the basic concepts of ns-2, set up their own network topologies and simulations, add traffic, run simulations, and use visualization tools.
Presentation by Mr. Vibin Chander, CEO, Shabari Software Solutions, CBE during the Faculty development Programm on NS2 organized by Department of Computer Science, Rathinam College of Arts and Computer Science (Autonomous), Eachanari, Coimbatore - 641021.
This document provides an introduction and overview of NS2 (Network Simulator 2). It discusses that NS2 is an open-source discrete event network simulator used to simulate TCP/IP networks. It describes the architecture of NS2 which uses C++ for internal operations and OTCL as the user interface. It also discusses the advantages of using Linux over Windows for NS2 and provides some basic Linux commands.
NS-2 is a discrete event network simulator used to model computer networks. It includes implementations of many common network protocols like TCP and various routing protocols. NS-2 uses C++ for core functionality and OTcl as a front-end for configuration and scripting. It models networks as nodes connected by links, with agents running protocols at each node. Users write OTcl scripts to define network topologies and scenarios that are then simulated to produce trace files for analysis.
This document provides an overview of network simulation using the Network Simulator 2 (NS2). It discusses the motivation for network simulation, what simulation is, and the advantages and drawbacks of simulation. It then describes the structure and programming of a simulation, including maintaining event lists and processing events. The document outlines NS2, including how to get it, create topologies, add traffic, observe behavior using NAM, and provides examples of simple NS2 scripts. It also briefly discusses adding new protocols to NS2 and finding documentation. The key points covered are the fundamentals and use of discrete event network simulation using the NS2 tool.
NS2 - the network simulator which is proved useful in studying the dynamic nature of communication networks. Simulation of wired as well as wireless network functions and protocols( e.g. routing algorithms, TCP, UDP ) can be done using NS2
Ns is an object-oriented network simulator written in C++ and OTcl that is used to simulate wired and wireless networks. It allows debugging of network protocols and configurations efficiently without physical equipment. Ns simulates network components, traffic models, transport and routing protocols, and physical media. It consists of an event scheduler that handles the simulation by processing events in chronological order.
The document provides an overview of installing and using the Network Simulator 2 (NS2). It discusses downloading and extracting NS2, setting up the Linux environment, understanding the basic NS2 architecture and directory structure. It also covers the differences between OTCL and C++ in NS2, and provides examples of creating a simple agent module in C++ and interfacing it with OTCL. The document includes a case study of building a multimedia application over UDP using NS2 that implements five different encoding and transmission rates.
This document provides an overview of Network Simulator 2 (NS-2) and how to use it to simulate computer networks. It discusses:
- The basic design of NS-2, which uses Tcl for scripting and C++ for implementing network objects. Simulation scripts are written in OTcl to set up the network topology and control packet transmissions.
- Common tasks in NS-2 like creating nodes and links, defining traffic sources and sinks, generating traffic patterns, and outputting trace files.
- Example scripts that demonstrate how to initialize a simulation, generate network traffic with different protocols (UDP, TCP), and visualize results using the Network Animator (NAM) tool.
- Key aspects of
The document provides an introduction and overview of the Network Simulator 2 (NS2). It outlines the components and basic requirements of NS2, describes how to install and set up a simple wireless network simulation involving 2 nodes, and explains how to run the simulation script. The simulation will generate a trace file that can be analyzed to test wireless routing and mobility protocols.
Presentation of Mr.Vibin Chander, CEO, Shabari Software Solutions, CBE. Delivered during the Faculty development Program on NS2 organized by Department of Computer Science, Rathinam College of Arts and Science (Autonomous), Eachanari, Coimbatore - 641021.
NS-2 is an open-source discrete event network simulator for networking research. It supports simulation of TCP, routing protocols and other network protocols. NS-2 includes both an OTcl interpreter for setting up simulations and C++ code for implementing network components and protocols. Simulations are run by executing OTcl scripts that create nodes, links, and traffic and schedule events over time.
Ns-2 is a discrete event network simulator used for modeling wired and wireless network protocols. It has two main components - the C++ simulator engine for fast packet-level processing, and the OTcl scripting language for configuration and control. Simulation involves setting up nodes, links, agents, applications and traffic before scheduling events and running the simulation. Traces can then be analyzed to evaluate network performance.
Ns is a network simulator developed at UC Berkeley and elsewhere that allows modeling of TCP/IP networks and wireless networks using C++ and OTcl. It provides objects for nodes, links, network traffic and wireless channel modeling. The document outlines how to install ns, create basic simulations with nodes and traffic, and extend it for wireless simulations using various protocols.
A short and fast journey through some of the profiling options available in the Ruby 2.x world, including a look at flamegraphs and new ways of tracking memory usage in the MRI.
This document provides information on setting up wireless simulations in NS-2 including:
1) Details on configuring wireless node parameters, channels, propagation models, interfaces, and routing protocols.
2) Examples of generating node mobility using the setdest script and generating traffic using cbrgen.
3) The format of DSR trace files and how to calculate routing overhead and packet delivery ratio from these files using AWK.
The document provides an overview of wireless sensor networks (WSNs), including their components, architecture, protocols, operating systems, simulators, challenges, features, and applications. It describes the basic components of a WSN including sensor nodes that contain sensors, processors, memory, transceivers, and power supplies. The document also outlines common WSN architectures like flat and hierarchical topologies. It discusses protocols, operating systems, and simulators used for WSNs like NS-2. Finally, it lists many applications of WSNs in fields such as healthcare, environment monitoring, and smart buildings.
This document defines options and sets up a simulation to test carrier sense in NS-2. It defines wireless channel, radio propagation, and MAC layer options. It creates 4 nodes with an 802.11 MAC and positions two nodes to have a conversation and the other two nodes some distance away to have another conversation. It generates CBR traffic between the node pairs and runs the simulation for 10 seconds.
The document provides an overview of the Network Simulator ns-2. It discusses:
1) The history and goals of ns-2 including supporting networking research, protocol design and comparison, and providing a collaborative environment.
2) Current projects using ns-2 including SAMAN to build robust networks and CONSER to extend ns-2's capabilities.
3) The components and functionality of ns-2 including modeling wired and wireless networks, various protocols, traffic sources, and queue management.
This document provides an introduction to using NS2 (Network Simulator 2) for network simulation. It recommends using Linux over Windows for NS2 as support has been stopped for Windows beyond a certain version. It outlines some basic Linux commands needed for working with NS2 and describes NS2's architecture which uses C++ for implementation and OTCL for the user interface with TclCL providing the interface between them. It also gives a brief overview of NS2's capabilities for simulating protocols and networking entities and describes OTCL with examples of defining classes and objects.
1. The document describes an ns-2 tutorial exercise on simulating computer networks using the ns-2 simulator. It provides example scripts for basic network simulations.
2. The example scripts simulate simple network topologies with increasing complexity, including UDP and TCP traffic over droptail and queue configurations.
3. Later examples introduce more complex scenarios like dynamic routing protocols and simulating link failures to observe network behavior.
- The document discusses the simulation and performance analysis of the AODV routing protocol for mobile ad-hoc networks using the NS-2.34 network simulator.
- It describes the basic principles and operation of AODV, the experimental setup used including varying parameters like node speed and number of connections, and the performance metrics measured like packet delivery fraction and routing overhead.
- The results of simulations run by varying these parameters are presented and analyzed to understand AODV performance under different conditions.
Новый InterSystems: open-source, митапы, хакатоныTimur Safin
Presentation for the 1st InterSystems Meetup in the Minsk:
- New and better InterSystems changes their practice.
- open-source repositories, meetups, and hackathon;
- CPM (package manager) as a good example of open-source project
Some of the biggest issues at the center of analyzing large amounts of data are query flexibility, latency, and fault tolerance. Modern technologies that build upon the success of “big data” platforms, such as Apache Hadoop, have made it possible to spread the load of data analysis to commodity machines, but these analyses can still take hours to run and do not respond well to rapidly-changing data sets.
A new generation of data processing platforms -- which we call “stream architectures” -- have converted data sources into streams of data that can be processed and analyzed in real-time. This has led to the development of various distributed real-time computation frameworks (e.g. Apache Storm) and multi-consumer data integration technologies (e.g. Apache Kafka). Together, they offer a way to do predictable computation on real-time data streams.
In this talk, we will give an overview of these technologies and how they fit into the Python ecosystem. As part of this presentation, we also released streamparse, a new Python that makes it easy to debug and run large Storm clusters.
Links:
* http://parse.ly/code
* https://github.com/Parsely/streamparse
* https://github.com/getsamsa/samsa
This document provides an introduction to DTrace and discusses its key features and capabilities. It covers:
1. What DTrace is and how it can be used to trace operating systems and programs with very low overhead.
2. The different ways DTrace can be used, including tracing system calls, kernel functions, user processes, and custom probes added to programs.
3. How DTrace scripts are structured using probes, filters, and actions. Variables that can be used like timestamps.
4. Examples of using DTrace to trace network activity by probe name, argument definitions, and creating DTrace programs.
Rust provides safe, fast code through its ownership and borrowing model which prevents common bugs like use-after-free and data races. It enables building efficient parallel programs while avoiding the need for locking. Traits allow defining common interfaces that can be implemented for different types, providing abstraction without runtime costs. The language also supports unsafe code for interfacing with other systems while still enforcing safety within Rust programs through the type system.
NS-3 is a discrete event network simulator written in C++ to simulate Internet systems. The document discusses using NS-3 to simulate and compare direct mapping and dynamic mapping in IPv6 address resolution. It generates results using network tools like Wireshark and tracing files to show that direct mapping improves IPv6 packet transmission time over dynamic mapping by extracting the MAC address directly from the IPv6 address rather than using neighbor discovery protocols. It concludes direct mapping is more efficient and suggests future works could add routers, more network traffic, and multicast to the simulation topology.
This document provides an overview of Network Simulator 2 (NS-2), an open-source discrete event network simulator targeted primarily for networking research and education. NS-2 was developed at UC Berkeley and is maintained by USC. It supports simulation of TCP, routing, and wireless protocols and includes models for network traffic, queues, and links. NS-2 uses both C++ for implementation of protocols and OTcl for configuration of simulation scenarios, allowing for detailed and flexible simulations. The document outlines the goals, architecture, usage, and extension of NS-2.
This document provides an introduction and overview of Network Simulator 2 (NS2). It discusses the history and goals of NS2, the languages and protocols it supports, and how to work with and extend NS2. It describes how to create simple simulations using Tcl scripts, including defining nodes, links, traffic sources and sinks. It also provides an example of simulating wireless networks in NS2 using scripts to define node movement and the DSDV routing protocol.
The document provides an overview of installing and using the Network Simulator 2 (NS2). It discusses downloading and extracting NS2, setting up the Linux environment, understanding the basic NS2 architecture and directory structure. It also covers the differences between OTCL and C++ in NS2, and provides examples of creating a simple agent module in C++ and interfacing it with OTCL. The document includes a case study of building a multimedia application over UDP using NS2 that implements five different encoding and transmission rates.
This document provides an overview of Network Simulator 2 (NS-2) and how to use it to simulate computer networks. It discusses:
- The basic design of NS-2, which uses Tcl for scripting and C++ for implementing network objects. Simulation scripts are written in OTcl to set up the network topology and control packet transmissions.
- Common tasks in NS-2 like creating nodes and links, defining traffic sources and sinks, generating traffic patterns, and outputting trace files.
- Example scripts that demonstrate how to initialize a simulation, generate network traffic with different protocols (UDP, TCP), and visualize results using the Network Animator (NAM) tool.
- Key aspects of
The document provides an introduction and overview of the Network Simulator 2 (NS2). It outlines the components and basic requirements of NS2, describes how to install and set up a simple wireless network simulation involving 2 nodes, and explains how to run the simulation script. The simulation will generate a trace file that can be analyzed to test wireless routing and mobility protocols.
Presentation of Mr.Vibin Chander, CEO, Shabari Software Solutions, CBE. Delivered during the Faculty development Program on NS2 organized by Department of Computer Science, Rathinam College of Arts and Science (Autonomous), Eachanari, Coimbatore - 641021.
NS-2 is an open-source discrete event network simulator for networking research. It supports simulation of TCP, routing protocols and other network protocols. NS-2 includes both an OTcl interpreter for setting up simulations and C++ code for implementing network components and protocols. Simulations are run by executing OTcl scripts that create nodes, links, and traffic and schedule events over time.
Ns-2 is a discrete event network simulator used for modeling wired and wireless network protocols. It has two main components - the C++ simulator engine for fast packet-level processing, and the OTcl scripting language for configuration and control. Simulation involves setting up nodes, links, agents, applications and traffic before scheduling events and running the simulation. Traces can then be analyzed to evaluate network performance.
Ns is a network simulator developed at UC Berkeley and elsewhere that allows modeling of TCP/IP networks and wireless networks using C++ and OTcl. It provides objects for nodes, links, network traffic and wireless channel modeling. The document outlines how to install ns, create basic simulations with nodes and traffic, and extend it for wireless simulations using various protocols.
A short and fast journey through some of the profiling options available in the Ruby 2.x world, including a look at flamegraphs and new ways of tracking memory usage in the MRI.
This document provides information on setting up wireless simulations in NS-2 including:
1) Details on configuring wireless node parameters, channels, propagation models, interfaces, and routing protocols.
2) Examples of generating node mobility using the setdest script and generating traffic using cbrgen.
3) The format of DSR trace files and how to calculate routing overhead and packet delivery ratio from these files using AWK.
The document provides an overview of wireless sensor networks (WSNs), including their components, architecture, protocols, operating systems, simulators, challenges, features, and applications. It describes the basic components of a WSN including sensor nodes that contain sensors, processors, memory, transceivers, and power supplies. The document also outlines common WSN architectures like flat and hierarchical topologies. It discusses protocols, operating systems, and simulators used for WSNs like NS-2. Finally, it lists many applications of WSNs in fields such as healthcare, environment monitoring, and smart buildings.
This document defines options and sets up a simulation to test carrier sense in NS-2. It defines wireless channel, radio propagation, and MAC layer options. It creates 4 nodes with an 802.11 MAC and positions two nodes to have a conversation and the other two nodes some distance away to have another conversation. It generates CBR traffic between the node pairs and runs the simulation for 10 seconds.
The document provides an overview of the Network Simulator ns-2. It discusses:
1) The history and goals of ns-2 including supporting networking research, protocol design and comparison, and providing a collaborative environment.
2) Current projects using ns-2 including SAMAN to build robust networks and CONSER to extend ns-2's capabilities.
3) The components and functionality of ns-2 including modeling wired and wireless networks, various protocols, traffic sources, and queue management.
This document provides an introduction to using NS2 (Network Simulator 2) for network simulation. It recommends using Linux over Windows for NS2 as support has been stopped for Windows beyond a certain version. It outlines some basic Linux commands needed for working with NS2 and describes NS2's architecture which uses C++ for implementation and OTCL for the user interface with TclCL providing the interface between them. It also gives a brief overview of NS2's capabilities for simulating protocols and networking entities and describes OTCL with examples of defining classes and objects.
1. The document describes an ns-2 tutorial exercise on simulating computer networks using the ns-2 simulator. It provides example scripts for basic network simulations.
2. The example scripts simulate simple network topologies with increasing complexity, including UDP and TCP traffic over droptail and queue configurations.
3. Later examples introduce more complex scenarios like dynamic routing protocols and simulating link failures to observe network behavior.
- The document discusses the simulation and performance analysis of the AODV routing protocol for mobile ad-hoc networks using the NS-2.34 network simulator.
- It describes the basic principles and operation of AODV, the experimental setup used including varying parameters like node speed and number of connections, and the performance metrics measured like packet delivery fraction and routing overhead.
- The results of simulations run by varying these parameters are presented and analyzed to understand AODV performance under different conditions.
Новый InterSystems: open-source, митапы, хакатоныTimur Safin
Presentation for the 1st InterSystems Meetup in the Minsk:
- New and better InterSystems changes their practice.
- open-source repositories, meetups, and hackathon;
- CPM (package manager) as a good example of open-source project
Some of the biggest issues at the center of analyzing large amounts of data are query flexibility, latency, and fault tolerance. Modern technologies that build upon the success of “big data” platforms, such as Apache Hadoop, have made it possible to spread the load of data analysis to commodity machines, but these analyses can still take hours to run and do not respond well to rapidly-changing data sets.
A new generation of data processing platforms -- which we call “stream architectures” -- have converted data sources into streams of data that can be processed and analyzed in real-time. This has led to the development of various distributed real-time computation frameworks (e.g. Apache Storm) and multi-consumer data integration technologies (e.g. Apache Kafka). Together, they offer a way to do predictable computation on real-time data streams.
In this talk, we will give an overview of these technologies and how they fit into the Python ecosystem. As part of this presentation, we also released streamparse, a new Python that makes it easy to debug and run large Storm clusters.
Links:
* http://parse.ly/code
* https://github.com/Parsely/streamparse
* https://github.com/getsamsa/samsa
This document provides an introduction to DTrace and discusses its key features and capabilities. It covers:
1. What DTrace is and how it can be used to trace operating systems and programs with very low overhead.
2. The different ways DTrace can be used, including tracing system calls, kernel functions, user processes, and custom probes added to programs.
3. How DTrace scripts are structured using probes, filters, and actions. Variables that can be used like timestamps.
4. Examples of using DTrace to trace network activity by probe name, argument definitions, and creating DTrace programs.
Rust provides safe, fast code through its ownership and borrowing model which prevents common bugs like use-after-free and data races. It enables building efficient parallel programs while avoiding the need for locking. Traits allow defining common interfaces that can be implemented for different types, providing abstraction without runtime costs. The language also supports unsafe code for interfacing with other systems while still enforcing safety within Rust programs through the type system.
NS-3 is a discrete event network simulator written in C++ to simulate Internet systems. The document discusses using NS-3 to simulate and compare direct mapping and dynamic mapping in IPv6 address resolution. It generates results using network tools like Wireshark and tracing files to show that direct mapping improves IPv6 packet transmission time over dynamic mapping by extracting the MAC address directly from the IPv6 address rather than using neighbor discovery protocols. It concludes direct mapping is more efficient and suggests future works could add routers, more network traffic, and multicast to the simulation topology.
This document provides an overview of Network Simulator 2 (NS-2), an open-source discrete event network simulator targeted primarily for networking research and education. NS-2 was developed at UC Berkeley and is maintained by USC. It supports simulation of TCP, routing, and wireless protocols and includes models for network traffic, queues, and links. NS-2 uses both C++ for implementation of protocols and OTcl for configuration of simulation scenarios, allowing for detailed and flexible simulations. The document outlines the goals, architecture, usage, and extension of NS-2.
This document provides an introduction and overview of Network Simulator 2 (NS2). It discusses the history and goals of NS2, the languages and protocols it supports, and how to work with and extend NS2. It describes how to create simple simulations using Tcl scripts, including defining nodes, links, traffic sources and sinks. It also provides an example of simulating wireless networks in NS2 using scripts to define node movement and the DSDV routing protocol.
The document describes how to simulate computer networks using the Network Simulator 2 (NS2). It discusses running NS2 on the department's Unix server and modifying configuration files. It then provides examples of simulating simple wired and wireless network topologies with different types of traffic including UDP and TCP. Trace files are analyzed to understand network performance.
The document provides an introduction to the Network Simulator 2 (NS2) by describing its components, architecture that separates C++ and OTcl, and basic usage including writing Tcl scripts to simulate simple network topologies and traffic patterns and analyzing trace files. It also gives examples of simulating simple wired and wireless networks with UDP and TCP traffic.
Ns is an open-source network simulator written in C++ and OTcl that allows debugging of wired and wireless network protocols. It provides an event-driven simulation environment where users can model networking scenarios without physical equipment. Ns simulations involve defining a network topology with nodes, attaching traffic source and destination agents to nodes using protocols like TCP and UDP, generating network traffic, and running the simulation. The results can be analyzed using trace files and visualized using the Network Animator (NAM) and Xgraph plotting tools.
Network simulator 2 :
Object-oriented, discrete event driven network simulator
It was normally used in wired & wireless protocol
Written in C++ and OTcl
This document provides an overview and introduction to network simulation using the NS-2 network simulator. It discusses the basics of discrete event simulation and the structure and components of NS-2 simulations. It covers topics like the advantages and drawbacks of simulation, programming a simulation, the event-driven structure of NS-2, examples of creating simple network topologies and adding traffic in NS-2 simulations.
This document provides an introduction and overview of NS-2, a discrete event network simulator. It discusses that NS-2 uses C++ for data and packet processing and OTcl for control and configuration. It also outlines some of NS-2's key capabilities like simulating wired and wireless networks, various protocols, and its use of events to drive simulation time forward. Examples of basic OTcl and Tcl commands are also provided.
This document provides an overview of the NS-2 network simulator. It discusses how NS-2 allows testing of complex network scenarios in a controlled and cost-effective manner compared to physical experiments. It describes key NS-2 features like support for various protocols, traffic models, and error models. It also outlines the object-oriented structure of NS-2 with its C++ backend and OTcl frontend and provides examples of configuring simulations involving nodes, links, traffic generation and capturing network events.
LF_OVS_17_OVS/OVS-DPDK connection tracking for Mobile usecasesLF_OpenvSwitch
1) Mobile networks today handle a large number of simultaneous short duration flows, with high call rates of 100k-200k connections per second. Statistics like call duration and bandwidth usage need to be tracked for each flow for billing purposes.
2) Testing was conducted injecting a 10Gbps mobile traffic profile of 1 million flows into OVS, with 200k flows created and destroyed per second. Key metrics measured were maximum throughput, latency, and jitter at different flow table sizes and core counts.
3) Conntrack performance was tested for OVS kernel and DPDK versions. For 100k flows, OVS kernel achieved 152k pps for 4-tuple matching while OVS-DPDK achieved
The document discusses techniques for conducting a "grey-box" attack on Windows and Linux systems. It covers scanning and enumeration of open ports and services using Nmap to identify vulnerabilities. It then discusses methods for gaining initial access, including exploiting the null session vulnerability in Windows 2000 to enumerate user accounts. It also discusses privilege escalation techniques to gain full control of compromised systems. The document provides examples using Nmap and Metasploit to automate vulnerability scanning and exploitation.
E2MATRIX Provide industrial training for all those students who want to learn software languages and methodology. We have all types of training programs as per the requirements of students. Our 6 Months Industrial Training Program is especially for last semester students of MCA, B. Tech., BE, M.sc, B.sc. Diploma etc. Students will work on LIVE PROJECTS during their 6 months industrial training. So why just go to any institute for training if you have an opportunity to learn from IT experts.
The document discusses the Network Simulator 2 (NS2) tool. It provides an overview of NS2's architecture, which uses C++ for the backend simulation objects and OTcl for the frontend setup. It also describes how NS2 simulations are run using a Tcl script to initialize objects, define the network topology with nodes and links, setup transport and application layer agents, schedule simulation events, and terminate the simulation. Key aspects covered include initializing and terminating the simulator, defining nodes and links, setting up TCP, UDP, and CBR agents, and scheduling the start and stop of applications.
This document summarizes a presentation on the network simulator NS2. It describes NS2 as a discrete event simulator used for networking research. The document provides background on the development of NS2 from 1995-1999. It discusses the platforms that support NS2, advantages such as being able to find bugs early, and drawbacks like requiring significant resources for large scale simulations. It also summarizes the key components of NS2 like the Network Animator NAM for visualizing simulations and the use of TCL and C++ in NS2 modeling.
Protocol T50: Five months later... So what?Nelson Brito
T50 (an Experimental Mixed Packet Injector) new features added to version 5.3 (Chaos Maker).
Check the original demonstration videos:
- https://www.youtube.com/playlist?list=PLda9TmFadx_m2qdd-euUf4zhQ-5juTVEx
For further source codes, please, refer to:
- http://t50.sourceforge.net/
P2P Online Storage aims to provide large, reliable, and secure distributed online storage by harnessing the idle resources of participating computers. It uses erasure coding to split files into fragments that are distributed across the network and stored redundantly to ensure availability even if some computers go offline. Access and sharing of encrypted files is enabled through a cryptographic access control system that provides privacy and prevents unauthorized parties from accessing files.
This document provides instructions and content for a computer network laboratory manual. It includes:
1. Instructions for students on preparation, maintaining records, obtaining signatures, and proper equipment use.
2. A table of contents listing experiments on topics like NS2 basics, point-to-point networks, wireless LANs, and algorithms.
3. An introduction to the NS2 network simulator, including its Tcl scripting language components, basic architecture, and how to initialize, define nodes/links, and configure agents and applications in a simulation.
The document summarizes how to simulate simple network topologies and traffic patterns using the ns2 network simulator. It provides examples of creating wired and wireless network simulations with nodes, links, and traffic including UDP and TCP. The tutorials cover basic simulations, adding traffic, analyzing traces, simulating link failures, and examining TCP performance over wireless networks.
Capturing NIC and Kernel TX and RX Timestamps for Packets in GoScyllaDB
Go gives us net.Dial and net.Listen for sending and receiving data at Layer 4. Now you will see how to send and receive raw packets directly to and from the NIC at Layer 1 to get timestamp information from timestamping-enabled NICs and when packets enter and leave the Linux kernel. Capturing these timestamps allows us to get better granularity when measuring latency and jitter instead of relying on time.Now() in userspace where that is subject to additional time introduced by the OS and Go runtime schedulers.
The document describes a network laboratory experiment on simulating a star topology using the NS2 simulator.
The objectives are to simulate the star topology, understand queuing and packet dropping at routers, and apply the knowledge to measure network performance metrics.
The steps include creating nodes and links to form the star topology, generating UDP traffic from two sources to a sink node, and observing packet dropping at the congested link using the nam trace file.
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
3. 3
ns-2, the Network Simulatorns-2, the Network Simulator
• AA discrete event simulatordiscrete event simulator modellingmodelling
network protocolsnetwork protocols
– Packets, links, queues, protocolsPackets, links, queues, protocols
– Visualizer (Visualizer (NAMNAM))
– Trace playbackTrace playback
– Error modelsError models
• Targeted at networking researchTargeted at networking research
• Supports for all types of simulationsSupports for all types of simulations
4. 4
HistoryHistory
• 1989:1989: REALREAL by Keshavby Keshav
• 1995:1995: nsns by Floyd, McCanne at LBLby Floyd, McCanne at LBL
• 1997:1997: ns-2ns-2 by the VINT projectby the VINT project
((Virtual InterNetwork TestbedVirtual InterNetwork Testbed) at) at
LBL, Xerox PARC, UCB, USC/ISILBL, Xerox PARC, UCB, USC/ISI
• 1999: Wireless models added @ CMU1999: Wireless models added @ CMU
• Now:Now: ns-2.29ns-2.29 maintained at USC/ISImaintained at USC/ISI
– ns-2.30ns-2.30 pending releasepending release
5. NS-2 OverviewNS-2 Overview
• TCP/IP NS2 OSI 7-LayerTCP/IP NS2 OSI 7-Layer
5
•Application
•Presentation
•Session
•Transport
•Network
•Data Link
•Physical
•Application
•Agent
•Node
•Link
•Application
•TCP/UDP
•IP
•Network
•Access
6. Platforms SupportedPlatforms Supported
• Most UNIX and UNIX-like systemsMost UNIX and UNIX-like systems
FreeBSDFreeBSD
LinuxLinux
SolarisSolaris
• Windows 98/2000/2003/XPWindows 98/2000/2003/XP
– Cygwin requiredCygwin required
– Some work , some doesntSome work , some doesnt
6
7. User’s PerspectiveUser’s Perspective
• From the user’s perspective, NS−2 isFrom the user’s perspective, NS−2 is
an OTcl interpreter that takes an OTclan OTcl interpreter that takes an OTcl
script as input and produces a tracescript as input and produces a trace
file as output.file as output.
7
9. 9
ComponentsComponents
• ns-2ns-2, the simulator itself, the simulator itself
– Specify simulation, generate tracesSpecify simulation, generate traces
– Depends on Tcl/Tk, OTcl, TclCLDepends on Tcl/Tk, OTcl, TclCL
• namnam, the network animator, the network animator
– Animate traces from simulationAnimate traces from simulation
– GUI for constructing simple simulationsGUI for constructing simple simulations
• Pre-processingPre-processing
– Traffic, topology generationTraffic, topology generation
• Post-processingPost-processing
– Analyse trace output withAnalyse trace output with awkawk, etc, etc
10. NS ModelsNS Models
• Traffic models and applications:Traffic models and applications:
– Web, FTP, telnet, constant-bit rateWeb, FTP, telnet, constant-bit rate
• Transport protocols:Transport protocols:
– unicast: TCP (Reno, Vegas, etc.), UDPunicast: TCP (Reno, Vegas, etc.), UDP
– Multicast: SRMMulticast: SRM
• Routing and queueing:Routing and queueing:
– Wired routing, ad hoc rtgWired routing, ad hoc rtg
– queueing protocols: RED, drop-tail, etcqueueing protocols: RED, drop-tail, etc
• Physical media:Physical media:
– Wired (point-to-point, LANs), wirelessWired (point-to-point, LANs), wireless
(multiple propagation models), satellite(multiple propagation models), satellite
10
11. Basic ArchitectureBasic Architecture
11
•An executable command ns
•Input: tcl simulation scripting file
•Output: trace file Animation by NAM or
plotting graph by Xgraph (gunplot)
12. NS2-GoalsNS2-Goals
To support networking research andTo support networking research and
educationeducation
–– Protocol design, traffic studies, etc.Protocol design, traffic studies, etc.
–– Protocol comparison;Protocol comparison;
–– New architecture designs are alsoNew architecture designs are also
supported.supported.
•• To provideTo provide collaborativecollaborative environmentenvironment
–– Freely distributed, open source;Freely distributed, open source;
–– Increase confidenceIncrease confidence in resultin result
12
14. 14
UsingUsing nsns
• Create simulationCreate simulation
– Describe network, protocols, sources, sinksDescribe network, protocols, sources, sinks
– Interface via OTcl which controls C++Interface via OTcl which controls C++
• Execute simulationExecute simulation
– Simulator maintains event list (packet list), executesSimulator maintains event list (packet list), executes
next event (packet), repeats until donenext event (packet), repeats until done
– Events happen instantly inEvents happen instantly in virtual timevirtual time but could takebut could take
arbitrarily longarbitrarily long real timereal time
– Single thread of control, no locking, races, etcSingle thread of control, no locking, races, etc
• Post-process resultsPost-process results
– Scripts (awk, perl, python) to process text outputScripts (awk, perl, python) to process text output
– No standard library but some available on webNo standard library but some available on web
15. 15
LanguagesLanguages
• C++ forC++ for datadata
– Per-packet processing, the core ofPer-packet processing, the core of nsns
– Fast to run, detailed, complete controlFast to run, detailed, complete control
• OTcl forOTcl for controlcontrol
– Simulation descriptionSimulation description
– Periodic or triggered actionsPeriodic or triggered actions
– Manipulating existing C++ objectsManipulating existing C++ objects
– Faster to write and change codeFaster to write and change code
» (a matter of opinion)(a matter of opinion)
16. 16
Basic TclBasic Tcl
# Variables:# Variables:
setset x 10x 10
setset xx
putsputs “x is $x”“x is $x”
# Functions and expressions:# Functions and expressions:
setset y [pow x 2]y [pow x 2]
setset y [expr x*x]y [expr x*x]
# Control flow:# Control flow:
ifif {$x > 0} {{$x > 0} { returnreturn $x }$x } elseelse {{
returnreturn [expr -$x] }[expr -$x] }
whilewhile { $x > 0 } {{ $x > 0 } {
putsputs $x$x
incrincr x –1x –1
}}
forfor {{setset i 0} {$i<10} {i 0} {$i<10} {incrincr i} {i} {
putsputs “$i == $i”“$i == $i”
}}
# Procedures:# Procedures:
procproc pow {x n} {pow {x n} {
ifif {$n == 1} {{$n == 1} { returnreturn $x }$x }
setset part [part [powpow x [x [exprexpr $n-1]]$n-1]]
returnreturn [[exprexpr $x*$part]$x*$part]
}}
# Files:# Files:
setset file [file [open “open “nstrace.txt” w]nstrace.txt” w]
setset line [line [getsgets $file]$file]
puts –nonewlineputs –nonewline $file “hello!”$file “hello!”
closeclose $file$file
17. 17
App1
Agent1
App2
Agent2
Node
From Network to SimulationFrom Network to Simulation
Application,
Agent & Node
LinkNode
App1
Agent1
App2
Agent2
Node
App1
Agent1
App2
Agent2
Node
App1
Agent1
App2
Agent2
Node
Node Node Node
Link
Link
Link Link
Link
Link
Link
Link
App1
Agent1
App2
Agent2
Node
App1
Agent1
App2
Agent2
Node
20. Elements for NS-2 simulationElements for NS-2 simulation
20
•Create the event scheduler
•Turn on tracing
•Create network
•Setup routing
•Create transport connection
•Create traffic
•Transmit application-level data
21. Creating Simulation environmentCreating Simulation environment
21
Create event scheduler
set ns [new Simulator]
Schedule events
$ns at <time> <event>
<event>: any legitimate ns/tcl commands
Start scheduler
$ns run
22. TracingTracing
22
Turn on tracing on specific links
$ns trace-queue $n0 $n1
$ns namtrace-queue $n0 $n1
23. Creating nodes, links and queuesCreating nodes, links and queues
23
Nodes
set n0 [$ns node]
set n1 [$ns node]
Links and queuing
$ns duplex-link $n0 $n1 <bandwidth> <delay>
<queue_type>
<queue_type>: DropTail, RED, CBQ, FQ, SFQ,
DRR
27. Creating Traffic : on top of TCPCreating Traffic : on top of TCP
27
FTP
set ftp [new Application/FTP]
$ftp attach-agent $tcp
Telnet
set telnet [new
Application/Telnet]
$telnet attach-agent $tcp
28. Simple Simulation ExampleSimple Simulation Example
28
•This network consists of 4 nodes (n0, n1, n2, n3)
•The duplex links between n0 and n2, and n1 and n2 have
•The duplex link between n2 and n3 has 1.7 Mbps of bandwidth and 20 ms of
delay 2 Mbps of bandwidth and 10 ms of delay.
•Each node uses a DropTail queue,of which the maximum size is 10
•ftp session is based on tcp
•tcp agent: generate packet (l=1k bytes)
•sink: generate ack and free packets
•cbr session is based on udp
•udp agent: generate packet (l=1k bytes)
@ 1 Mbps
•null: free packets
what is it?
-- history
-- code stats
-- tree layout
goals, accomplishments, status
ns architecture/history/perspective
target audience, tutorial outline
state of the software and distributions
what does it do?
-- tcp, higher protocols, packets, links, queuing disciplines
-- visualizer (NAM)
-- trace playback
-- error models
what does it not do?
-- routing, ip, L2, routing
basic structure
-- setup simulation
-- objects -&gt; events -&gt; schedule -&gt; repeat
-- trace files -&gt; post processing -&gt; graphs
-- (example trace)
Model world as events
Simulator has list of events
Process: take next one, run it, until done
Each event happens in an instant of virtual (simulated) time, but takes an arbitrary amount of real time
Ns uses simple model: single thread of control =&gt; no locking or race conditions to worry about (very easy)