network simulator (NS-2)

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Study of the Implementation of Ad hoc On Demand Distance Vector (AODV) Protocol in Network Simulator (NS 2)

Study of the Implementation of Ad hoc On Demand Distance Vector (AODV) Protocol in Network Simulator (NS 2)

Network Simulator Version 2, also known as NS-2. It is an event driven packet level network simulator developed as part of the VINT project (Virtual Internet Test bed). It was a collaboration of many institutes including UC Berkeley, AT&T, XEROX PARC and ETH. Version 1 of NS was developed in 1995 and with version 2 released in 1996. Version 2 included a scripting language called Object Oriented Tcl (OTcl). It is an open source software package available for both Windows 32 and Linux platforms. The open source network simulation tool ns-2 is an invaluable tool for researchers working on wired or wireless networks. ns-2 is a variant of the REAL network simulator. Over the past few years it has been evolving, and it is still far from complete. Several organizations have been involved in its development, including DARPA, Xerox, UCB, and Sun Microsystems. The objective has been to make a network simulation tool to study and analyze new ideas in detail before implementation.

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Network Simulator 2 [roland] pdf

Network Simulator 2 [roland] pdf

$ns duplex-link $node_(0) $node_(5) 2Mb 2ms $opt(qType) $ns duplex-link $node_(5) $node_(6) 2Mb 2ms $opt(qType) $ns duplex-link $node_(6) $node_(7) 2Mb 2ms $opt(qType) $ns duplex-link $node_(6) $node_(8) 2Mb 2ms $opt(qType)

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Congestion Avoidance in Packet Networks using Network Simulator-3 (NS-3)

Congestion Avoidance in Packet Networks using Network Simulator-3 (NS-3)

There are 4 nodes N0, N1, N2 and N3, at the left side of bolttleneck link, sending data to the same node i.e N4. This node is acting as an RED or Adaptive RED router as per configuration. As all the clients are sending data to the same node, a queue will be built up called as RED queue. The queue length and average queue length of the queue have also been analyzed. The packets are then further being transmitted to node N5 that is the final destination for packet transmission. The following figure shows the network configuration on Network Animator of NS-3.

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An XG PON Module for the NS 3 Network Simulator

An XG PON Module for the NS 3 Network Simulator

As shown in Figure 1, PON is a point-to-multipoint fiber network and there are three kinds of equipment: the OLT (Optical Line Terminal) in central office, ONUs (Optical Network Unit) in/near customer premise, and passive opti- cal splitters/jointers in the middle. Through splitter/jointer, OLT and the feeder fiber are shared by multiple users. Com- pared with the point to point architecture, PON can signif- icantly reduce the amount of required optical fibers and the central office equipments. Since the passive optical split- ters/jointers do not need power supply, the cost of deploy- ment, maintenance and operation can also be reduced. Thus, PON could reduce both capital expenditure and operational expenditure significantly.

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Network Simulator Version 2 for VANET

Network Simulator Version 2 for VANET

1) Edit packet.h file: We need a new packet type for our MyPing agent, therefore the first step is to modify the “$NS/common/packet.h” file (assuming that the $NS environment variable points the …./ns-allinone- 2.31/ns-2.31 location). There you can find the definitions for the packet protocol IDs (i.e. PT_TCP, PT_TELNET, etc.). Add a new definition for PT_PING there. In my edited version of packet.h, the last few lines of enum packet_t{} looks like the following code (it might look a bit different in different NS releases). You also have to edit the p_info() in the same file to include "MyPing".

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Study the effect of number of nodes in large scale 
		Wireless Sensor 
		Networks with design GUI support tools

Study the effect of number of nodes in large scale Wireless Sensor Networks with design GUI support tools

The Wireless Sensor Networks (WSN) has a limited power supply because each node was equipped with a battery. In most situations, they are deployed in a hostile environment where it is exceptionally hard to change or charge their batteries. Because of this, it becomes challenging in WSN to prolong the system lifetime and at the same time achieve a better throughput. The number of nodes in the network is regarded as the most significant factor in the WSN performance. Therefore, the current paper aimed to study the effect of the number of nodes on the performance of WSN. Quality of service (QoS) performance metrics in the study were network lifetime, energy dissipation and throughput in a different number of nodes. In addition, during the study, we proposed and implemented the graphical user interface (GUI) tools to generate the Network Simulator 2 (NS-2) script code for topology scenario file, and the graph tools (GT) to plot the NS-2 simulation results. The visual basic language was used to design the GUI for generating the NS-2 script code while MATLAB was used to design the GT. Simulation experiments were conducted using NS-2.34 with Massachusetts Institute of Technology (MIT) extension LEACH protocol for a different number of nodes. We conclude that the increasing number of nodes can cause decreasing the throughout and consuming high energy, hence, resulting in the reduction of network lifetime.

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Improving Performance of Ad Hoc On-demand Distance Vector (AODV) Routing Protocol in Wireless Sensor Network

Improving Performance of Ad Hoc On-demand Distance Vector (AODV) Routing Protocol in Wireless Sensor Network

Network simulator (NS-2) [10] is used to evaluate the performance differences of AODV and EN-AODV. Simulation is set up with 802.11 wireless channel and 802.11 Mac at the physical and data link layer. Nodes move randomly within the 1200× 1000 area with various speed for about 200 seconds.FTP (file transfer protocol) applications of TCP are generated with default TCP window size 32 and the packet size 512 bytes. The initial energy of nodes is set to 500 joules. The parameters for analysis are listed in Table. The performance of modified AODV is studied under varying condition of the traffic load.

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OPTIMAL PARAMETERS SELECTION TO REDUCE CUTTING TEMPERATURE OF MILD STEEL USING 
PARTICLE SWARM OPTIMIZATION INTELLIGENT TECHNIQUE

OPTIMAL PARAMETERS SELECTION TO REDUCE CUTTING TEMPERATURE OF MILD STEEL USING PARTICLE SWARM OPTIMIZATION INTELLIGENT TECHNIQUE

Cognitive radio is emerging as an effective solution against the spectrum scarcity issue. The main processes which make up the cognitive radio working are the spectrum sensing, learning and adapting procedures. Co-operative sensing is a method in which the nodes share the spectrum sensed data. In ad-hoc network the decentralized nature makes it quite difficult to gather sensing data with constraints like energy consumption, shadowing, hidden terminal and fading effect. In cognitive radio ad-hoc network these effects creates issues in spectrum allocation and management. In this paper, the hidden terminal issue is considered with the solution of adaptive sensing range in a static network. The nodes in the ad-hoc network have sensing and transmitting ranges. The sensing helps to gain knowledge about the channels which are occupied by overhearing the RTS/CTS or ACK transmission or reception by the nearby nodes. The sensing range of a node is always greater than the transmitting range of a terminal. The sensing range if varied as per the transmission to the receiver then hidden node issue can be dealt to a great level. With the help Cognitive radio Network Simulator (CR-NS) adaptive sensing is simulated for an ad-hoc network and also its effect on throughput, packet loss, normalized routing load, end-to-end packet delay is also compared with respected to a fixed sensing environment.

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Survey on Network Simulators

Survey on Network Simulators

In computer networking, network simulation is a technique in which software program analyzes the behavior of a network by computing the association between different network devices/entity such as the hub, switch, router, access points, links etc. Network simulator provides visualization, animation of flow of packets, the performance of the network and cost- effective technique to design network. There are two types of simulators available, commercial and open source. The following paper presents both type of simulators and some comparative study between them. The following paper discusses various simulators such as Ns-2, Ns-3, OMNeT++, NetSim, REAL, OPNET and QualNet. Out of these varieties of simulators, it is difficult for one to select network simulator based on the requirement for a specific job. For each simulators mention above, the brief introduction, advantages, disadvantages, backend environment, the supporting operating system, minimum hardware requirement and comparison with other simulator is discussed. So based on above-mentioned information and analysis, one can make choice of an appropriate network simulator based on the requirements.

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DESIGN OF FRACTAL ANTENNA FOR UWB APPLICATIONS

DESIGN OF FRACTAL ANTENNA FOR UWB APPLICATIONS

A few numbers of packets are locked in the network for random time periods may occur due to the mobility of nodes in Mobile Ad hoc networks, “This problem may leads to packet drop, as it stays longer time peri- od in the loop than the allowable Time to Live (TTL) value”. The objective of the paper is to provide Loop- Free Multipath routing to reduce the packet drop and hence the network performance will be enhanced. In this paper, our proposed work of “Loop-free Multipath Probabilistic Scheme based AODV (LMPSAODV)” is simulated using network simulator NS-2.34 to evaluate network performance and the results are present- ed on various scenarios in terms of packet delivery ratio (PDR), total dropped packets, routing overhead, end-to-end delay and retransmission rate. The performance will be measured with two different TCP vari- ants namely TCP Tahoe and SACK. Each TCP variant uses different ways of congestion control algorithm. The simulation result shows that “the performance of LMPSAODV with TCP SACK performs better to the changing network sizes”.

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A Review of Simulation Techniques for Some Wireless Communication System

A Review of Simulation Techniques for Some Wireless Communication System

Abstract – Prior to live implementation or deployment of a communication system there is need for thorough testing. However, the environment to carry out the required test for either or both wired and wireless is not readily available. Therefore, the best option is to use a computer Simulator before live deployment. There are quite a number of computer simulators for wired/ wireless communication system. Among them, some are designed mainly for wireless network and others for both wired and wireless network. In this research work an extensive review of the simulation techniques used for wireless communication system was investigated to aid network and communication expert ascertain an appropriate simulator suitable for their proposed research. A review of REAL Network Simulator, Network Simulator -2 (NS-2), Network Simulator-3 (NS-3), Network Simulator (NetSim), OMNet++, JavaSim (J-Sim), ManaSim, SensorSim, NRL SensorSim and National Chiao Tung University Network Simulator (NCTUns) is presented along with their respective features with a sample wireless simulation to assist researchers in complex Wireless Communication researches.

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Adding TCP-Variants to NS-2

Adding TCP-Variants to NS-2

The network simulator (NS-2) is very important to simulate the network types such as mobile ad-hoc network efficiently and easily by providing the environment of this network exactly. This simulator helps the researcher in the last years to introduce Their researches without need to the expensive requirements to build the network in real time. This simulator uses file (called cbegen.tcl) to generate the traffic between nodes of the network at random time according to uniform distribution. The original cbrgen.tcl file provides two types of traffics that are CBR with UDP and FTP with TCP. The purpose of this paper is to add the one-way TCP and two-way TCP variants to NS-2. Also, this paper made these variants operate with many types of sink such as TCPSink, TCPSink/DelAck, TCPSink/Sack1, and TCPSink/Sack1/DelAck. This addition make it usable for anyone that wants to study the behaviour of these variants and its effects on the network.

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Design, Development and Testing of Parking Availability System Based on Vehicular Ad hoc Network

Design, Development and Testing of Parking Availability System Based on Vehicular Ad hoc Network

In this paper, a new VANET-based friendly and efficient parking scheme for large parking lots is designed, developed and tested using network simulator NS-2.With friendly parking scheme, RSUs installed across a parking lot can survey the whole parking lot, and provide two convenient services for drivers: 1) real-time parking navigation,2) friendly parking information dissemination. Extensive simulations have also been conducted to demonstrate that the proposed scheme can efficiently reduce the searching time delay for an available parking space, and subsequently save the fuels and driver’s parking time. In this paper simulation of Vehicular Ad-Hoc Network used for friendly parking system is implemented and tested satisfactory. Different test cases are generated to test the system and performance of AODV protocol for its throughput is also tested for efficiency of the system. With the help of this simulation we can conclude behavior of friendly parking system in different situations.

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Analyzing Performance of Zone Routing
          Protocol by Varying Node Density and
          Transmission Range

Analyzing Performance of Zone Routing Protocol by Varying Node Density and Transmission Range

Proactive routing uses excess bandwidth to maintain routing information, while reactive routing involves long route request delays. Reactive routing also inefficiently floods the entire network for route determination [2]. The Zone Routing Protocol (ZRP) aims to address the problems by combining the best properties of both approaches. ZRP can be classed as a hybrid reactive/proactive routing protocol. [12] In an ad-hoc network, it can be assumed that the largest part of the traffic is directed to nearby nodes. Therefore, ZRP reduces the proactive scope to a zone centered on each node. In a limited zone, the maintenance of routing information is easier. Further, the amount of routing information that is never used is minimized. Still, nodes farther away can be reached with reactive routing. Since all nodes proactively store local routing information, route requests can be more efficiently performed without querying all the network nodes. [12].

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PERFORMANCE ANALYSIS OF HORIZONTAL HANDOFF IN Wi-Fi AND WIMAX WIRELESS NETWORKS

PERFORMANCE ANALYSIS OF HORIZONTAL HANDOFF IN Wi-Fi AND WIMAX WIRELESS NETWORKS

Wireless network technology has gained the popularity due to its ability to provide the ubiquitous information access to the users on the move. In wireless networks mobile users are connected to the best available networks that are best fit according to their service requirement. Efficient mobility management is required to support mobility across the access networks, where the handoff is main element of mobility management. Handoff maintains

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Impact of Black Hole Attack on AODV Routing Protocol

Impact of Black Hole Attack on AODV Routing Protocol

The results of the simulation show that the throughput in the network with a Blackhole node decreases by increasing the number of blackhole nodes in the network. It is obvious that the throughput for the case with AODV, without attack, is higher than the throughput of AODV under attack as also shown in figure 1. The throughput keeps on decreasing as the numbers of malicious nodes are increased in the network keeping the total number of nodes constant in each scenario. This is because of the fewer routing forwarding and routing traffic. Here the malicious node discards the data rather than forwarding it to the destination, thus effecting throughput.

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Network Analyzer and Report Generation Tool for NS 2 using TCL Script

Network Analyzer and Report Generation Tool for NS 2 using TCL Script

In proposed system I have developed a new TCL script generator tool, named “ARGT for NS2”, to get authority users to generate Tool Command Language (TCL) scripts file in a direct and flexible way and it has Graphical User Interface (GUI). This tool has a very user-friendly interface to make wired as well as wireless communication design network constraints. After the parameters or constraints are entered, the tool is repeatedly created TCL scripts file, which can be run in the NS-2 communication network atmosphere forgives the network simulation output in the form of simulation for the provided network scenarios which being studied [1].

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Introducing a Distance Vector Routing Protocol for ns-3 Simulator

Introducing a Distance Vector Routing Protocol for ns-3 Simulator

The ns-3 simulator [21] is a discrete-event simulator, and was proposed as the eventual replacement of the ns-2 simula- tor [8]. The ns-3 simulator uses ns3::NetDevices to connect ns- 3::Nodes, because the ns3::NetDevices emulate physical network cards and the ns-3::NetDevices possess both Layer-3 IP and Layer- 2 MAC addresses. Two ns3::NetDevices are connected using an ns3::Channel, which represents a network communication medium (wired or wireless links) [20]. Furthermore, ns-3 supports most generic real-world packet structures, and the packets are serialized and de-serialized as they traverse the network stack [3]. In addi- tion, ns-3 supports both IPv4 and IPv6 addressing schemes. These features make ns-3 simulator an ideal simulator, which provides a more realistic and real-world-like simulation environment [19, 20]. Despite its advantages, ns-3 is still a new simulator and new models are currently being developed and incorporated into ns-3 distributions [5,16–18,23,25,26,28]. Because ns-3 was introduced to simulate real-network-like simulations, ns-3 must support rout- ing protocols for realistic evaluations of networks. A routing proto- col is necessary to maintain routes despite changes in network con- nections [7, 13]. In [2], Brakmo et al. theorized that most practical networks exhibit extremely complex behavior because of: 1) suit- able protocol interaction, 2) complicated network topologies, and 3) complex tra ffi c patterns. Moreover, according to [2,6,7,9,13,26], a routing protocol is directly related to the performance of a net- work. However, thus far, ns-3 does not comply with any Ipv4 wired routing protocol modules. This limitation limits the ability to sim- ulate and analyze network topologies such as CDNs [22, 27] on the ns-3 simulator.

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GRAPH PATTERN MATCHING IN YEAST DATASET

GRAPH PATTERN MATCHING IN YEAST DATASET

Some research studies in the literature have focused on studying the effect of malicious nodes on network performance only without providing any solutions. However, several mechanisms and protocols using different strategies have been proposed to protect MANETs against black hole attacks. In [6] the authors studied the effect of malicious attacks in mobile ad hoc networks including black hole attack, packet drop attack and gray hole attack on AODV protocol under different performance metrics: throughput, packet drop rate and end-to-end delay. It was found that the black hole attack is more dangerous than other attacks conducted in this paper.

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Content aware radio resource management for IMT advanced systems

Content aware radio resource management for IMT advanced systems

As an alternative, we can also use Jperf which is the GUI-based version of Iperf. Jperf is a graphical front-end for the network testing tool Iperf. It can be used to determine the maximum network throughput of a WAN or LAN connection. Furthermore, the tests results are automatically graphed and displayed in a presentable format. Similar to Iperf, Jperf can also be used to measure packet loss, throughput and jitter. Jperf offers many advantages over Iperf for its reliability and ease of use, whereas Iperf is a command line driven application. The first step before Jperf can be installed on Microsoft Windows, for example, is to install the pre-requisite software, which is Java version 1.5 or later. Only then, do we download the Jperf-2.0.2.zip file from the Jperf Google code webpage. Next, we extract the contents of the zip file into a folder located on the computer or laptop’s hard-drive without using an installer. Finally, we run the executable jperf.bat file to launch the Jperf utility [97]. Owing to the advantage of having a user-

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