Ns2 cognitive radio mac protocol

Volume 14, Number 1, January 12222
  1. Ns2 Vanet Examples
  2. Contributed Code
  3. Share your Details to get free
  4. Much more than documents.

Nov 4, Ns2 vs Ns3[ns2 ns3]. Network Simulator 3 - NS3. So, there is another way available if you want to install ns2 in that version. NS2 is a name for series of discrete event network simulators like ns-1, ns-2, and ns We'll assume this is your home directory. The results are in! See what nearly 90, developers picked as their most loved, dreaded, and desired coding languages and more in the Developer Survey. We also make observations on. Run the First nam example I. The goal of the exercise is to make the students familiar with ns2 simulator as well as TCP's congestion control and performance.

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  • NS2 Extension for Multi-Channel MAC Simulation Model.
  • What is Cognitive Radio?.

Modularity of simulation elements results in a compact simulation model, ns-2 does not waste resources of the platform in vainCompact. In order to generate a trace file. Network simulators are tools used to simulate discrete events in a network which helps to predict the behavior of a computer network. Ns3 info solution is an authorized research and project center, introduces itself as leading academic project center ensures optimal knowledge transfer, deliver projects in a unique way and provide enrichment quality oriented research and technical writing support for various research scholars.

Basic Architecture of NS2 Tcl scripting. Chapter 2 provides an overview of Network Simulator 2 NS2. The control simulation module is developed based on Matlab and is able to process data in the presence of network delays or lost packets. Ns provides substantial support for simulation of TCP, routing, and multicast protocols over wired and wireless local and satellite networks. Our concern does update project title every year. The Imunes-network simulator is one of the best alternatives to live experimental networks.

In general, NS2 provides users. Simulation is used for data networking and by it helps researchers to resolve queries in time and in minimal cost.

Ns2 Vanet Examples

Install this update to copy a local version of key help topics available in the d-deDUOnline Helpd. Network Simulator-2 ns-2 [23] is an open source, discrete event network simulator. Section IV gives overview of simulation of proposed method using NS2 simulator. All are discrete-event computer network simulators, primarily used in research and teaching.

Furthermore, the purpose is to give. Fading channels — Rayleigh Fading. Simulation Results. The OTcl script construction steps are explained by the implementation of DiffServ architecture to ns-2 simulator. Files are available under licenses specified on their description page. The network simulation tool aims at realistic network topology framework.

Hi Folks, In this post i am posting a sea of network simulator NS2 reading material files and resources that i have collected over the years.

Contributed Code

Network Simulations Using NS2 Introduction Network simulation software enable us to predict behavior of a large-scale and complex network system such as Internet at low cost under different configurations of interest and over long period. Ns provides substantial support for simulation of TCP, routing,. A packet classifier determines this. At the same time, cognitive wireless transceivers of SU are assumed half duplex.

Multipath propagation and Doppler effects in wireless environment are major factors of channel changes. Multipath propagation is relevant to the surrounding wireless channel links. Doppler effects are relevant to carrier frequency and relative movement rate of transceivers. Influenced by the above factors, it is difficult to collect the real-time quality condition of channels. The focus of this paper lies in attack behaviors of malicious nodes under the same channel condition. Therefore, the throughput of each channel is assumed the same.

If there is no special instruction, secondary users are called nodes. In CRN route, node trust is defined as the reliability that nodes honestly forward data packets to the next hop.

In centralized collaborated spectrum sensing, each SU reports the local sensing information to SU base station also called fusion center and SU base station is used for fusion decision of spectrum availability. However, this paper introduces trust mechanism into distributed CRN route and each node maintains channel information for the next hop to send data packet to monitor whether the next hop normally forwards data packets.

This paper uses the statistics of node forwarding behaviors and the beta reputation system to construct the trust of neighboring node j from node i. In this way, malicious nodes can be identified and selective forwarding attack can be defended so as to enhance the robustness of route mechanism. Below is the detailed description of how to calculate the node trust by the beta reputation system in distributed CRNs. The beta distribution usually is used to represent the posterior probability of one binary event. The probability expectation of the beta distribution is shown as Formula 2.

For binary events with two results , r represents the occurrence times of result x ; s represents the occurrence times of result.

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Through the setting in Formula 3 , the occurrence probability density of result x of the current binary event can be expressed as the function of historical statistic results. The only significance is to calculate the probability expectation of p in Formula 2. In CRN route, the beta reputation system takes the behaviors of node forwarding data packet as binary event of the beta distribution modeling.

From node i , if neighboring node j successfully forwards data packet to the next hop, it is noted as x ij ; if not, it is noted as. The times of successful forwarding and failed forwarding respectively are noted as r ij and s ij. Trust T ij of node i to neighboring node j represents the probability expectation that neighboring node forwards data packet to the next hop, shown as Formula 4.

At the same time, aside from direct trust evaluation between nodes, indirect trust evaluation of the to-be-evaluated nodes shall be collected from other neighboring nodes. This can be realized by collecting r and s information provided by other neighboring nodes. The statistic results of the existing forwarding behaviors of node i to neighboring node j are noted as and. The newly successful forwarding times and failed forwarding times are calculated according to Formula 5 and Formula 6.

When the indirect trust evaluation is integrated into trust calculation, its reliability must be considered. The nodes of the third party that provides indirect trust evaluation may provide false information and deliberately defames good nodes or overstates malicious nodes.

diefacotopo.cf Formula 7 and Formula 8 respectively define I r kj and I s kj. Indirect trust is endowed with certain weight to decrease the influence of false evaluation. After node i calculates the trust of all neighboring nodes, neighboring nodes are divided into trusted nodes, common nodes and malicious nodes according Table 1. Furthermore, the dynamic distinguishing boundaries of malicious nodes, common nodes and trusted nodes can be formed.

In multi-hop CRNs, the neighboring nodes of communication must own the same available channel. The channels of each link on the path from source nodes to destination nodes vary a lot. In this way, on-demand routing scheme is a good choice. At the same time, it is inevitable to face multi-channel switching problems in cognitive radio networks. Path delay becomes an important indicator of routing protocol design and routing optimization.

Background of Cognitive Radio

In Literature [ 22 ], the cumulative delay along a route is derived by path delay and node delay, which represent the delay of spectrum assigned along the route and the delay of spectrum assigned around each node on the route, respectively. The effectiveness of candidate routes is evaluated by the cumulative delay. However, nodes' malicious behavior has not been considered. Shown as Fig 2 , TSRM includes 5 modules, route discovery module, route reply module, route decision module, trust evaluation module and route maintenance module and each module contains several functions.

Based on the function of trust evaluation module, route discovery module and route reply module can find all the available paths from source nodes to destination nodes. Based on path delay and trust, route decision module selects optimal route. Route maintenance module guarantees the real-time performance of information to decrease the unreachable probability of data packets.

When the data packet of node i needs to be sent to destination node j but there is no route reaching destination nodes in the routing list of node i , one route discovery progress will be triggered. RREQ is sent to common nodes and trusted nodes of neighboring node i through common control channel to avoid malicious nodes to participate in data forwarding.

If there is no intersection or message received from malicious nodes, this message shall be abandoned. After other middle nodes receive RREP, the processing is the same as the above. The path accumulation delay D route,i of node i to destination node is shown as Formula Where, DP i represents the path delay from node i to destination node and DN i represents the sum of data transmission delay from node i to the destination node. For available routing path P , its path accumulation delay D route,i from source node i to the destination node is noted as D P , shown as Formula Suppose there are two available paths a and b.

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The corresponding path trust and path accumulation delay respectively are noted as T a , D a and T b , D b. The route decision is carried out according to the algorithm flow chart in Fig 3. If there are three available routing paths, all the possible values of path trusts and accumulation delays of them are detected.

Except when there are two or more same path trusts and accumulation delays or all the accumulation delays are 0, there is always one available path better than the other two. Then the left paths are compared according to Algorithm 1 until the last one, namely, the optimal routing path is selected. At this time, data are transmitted. When malicious behaviors information is sent to other neighboring nodes and source nodes, the neighboring nodes update their trust evaluation and source nodes restart route discovery or route decision.

At the same time, nodes periodically delete outdated route information in buffer memory for better management of buffer memory and update of routing information. When nodes are in the selective forwarding attack, their failed forwarding times increases gradually in view of neighboring nodes, which makes the trust evaluation calculated from Section 2. In the route discovery, malicious nodes will not receive RREQ and data forwarding will not pass malicious nodes.