An Approach to Analyze Behavior of Network Events in NS2 and NS3 Using AWK and Xgraph

Patel, Radhika; Patel, Nehal; Patel, Sandip

doi:10.1007/978-981-13-0586-3_14

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…That is why we score NS-3 with a high support level of development tools Table 1. Besides, NS-3 shows better performance (less memory and CPU is required) when compared with NS-2 [18], [19]. On the other side, OMNeT++, which is mainly used to build network simulations, is not actually defined as a network simulator but rather as a general-purpose discrete event-based simulation framework.…”

Section: Analysis Of Available Tools To Handle Large-scale Simulationsmentioning

confidence: 99%

Large-Scale Simulations Manager Tool for OMNeT++: Expediting Simulations and Post-Processing Analysis

et al. 2020

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Usually, simulations are the first approach to evaluate wireless and mobile networks due to the difficulties involved in deploying real test scenarios. Working with simulations, testing, and validating the target network model often requires a large number of simulation runs. Consequently, there are a significant amount of outcomes to be analyzed to finally plot results. One of the most extensively used simulators for wireless and mobile networks is OMNeT++. This simulation environment provides useful tools to automate the execution of simulation campaigns, yet single-scenario simulations are also supported where the assignation of resources (i.e., CPUs) has to be declared manually. However, conducting a large number of simulations is still cumbersome and can be improved to make it easier, faster, and more comfortable to analyze. In this work, we propose a large-scale simulations framework called simulations manager for OMNeT++ (SMO). SMO allows OMNeT++ users to quickly and easily execute large-scale network simulations, hiding the tedious process of conducting big simulation campaigns. Our framework automates simulations executions, resources assignment, and post-simulation data analysis through the use of Python's wide established statistical analysis tools. Besides, our tool is flexible and easy to adapt to many different network scenarios. Our framework is accompanied by a command-line environment allowing a fast and easy manipulation that allows users to significantly reduce the total processing time to carry out large sets of simulations about 25% of the original time. Our code and its documentation are publicly available at GitHub and on our website.INDEX TERMS Large-scale simulations, OMNeT++, results post-processing.

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Section: Analysis Of Available Tools To Handle Large-scale Simulationsmentioning

confidence: 99%

Large-Scale Simulations Manager Tool for OMNeT++: Expediting Simulations and Post-Processing Analysis

et al. 2020

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“…The cost of building a real distributed testing environment is very high. Simulation is an important method in network research, as simulation can be used to analyze network related problems under different protocols, cross traffic and topologies with much less cost [22][23][24]. The most wellknown network simulator is NS2.…”

Section: Simulationmentioning

confidence: 99%

A comprehensive study of distributed Denial-of-Service attack with the detection techniques

Ibrahim

Hamzah

Qasim

et al. 2020

IJECE

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With the dramatic evolution in networks nowadays, an equivalent growth of challenges has been depicted toward implementing and deployment of such networks. One of the serious challenges is the security where wide range of attacks would threat these networks. Denial-of-Service (DoS) is one of the common attacks that targets several types of networks in which a huge amount of information is being flooded into a specific server for the purpose of turning of such server. Many research studies have examined the simulation of networks in order to observe the behavior of DoS. However, the variety of its types hinders the process of configuring the DoS attacks. In particular, the Distributed DoS (DDoS) is considered to be the most challenging threat to various networks. Hence, this paper aims to accommodate a comprehensive simulation in order to figure out and detect DDoS attacks. Using the well-known simulator technique of NS-2, the experiments showed that different types of DDoS have been characterized, examined and detected. This implies the efficacy of the comprehensive simulation proposed by this study.

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Centralized Multicasting AODV Routing Protocol Optimized for Intermittent Cognitive Radio Ad Hoc Networks

Phaswana

Velempini

2023

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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An Approach to Analyze Behavior of Network Events in NS2 and NS3 Using AWK and Xgraph

Cited by 4 publications

References 2 publications

Large-Scale Simulations Manager Tool for OMNeT++: Expediting Simulations and Post-Processing Analysis

Large-Scale Simulations Manager Tool for OMNeT++: Expediting Simulations and Post-Processing Analysis

A comprehensive study of distributed Denial-of-Service attack with the detection techniques

Centralized Multicasting AODV Routing Protocol Optimized for Intermittent Cognitive Radio Ad Hoc Networks

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