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At the end of report, you need to discuss the following questions:

1. Why queues are important in communication and networking.


2. What is the difference between stack and queues

3. Explain M/M/1 notation and further discuss following cases-G/M/1, M/D/1, D/D/1

4. What is difference between passive and active queues

5. What are the main parameters which control traffic generation by traffic sources in network simulators

6. What is a traffic classifier and its importance

Quality of Service in OPNET Simulator

The Quality of Service works on the overall performance where the quality of service is related to the error rates, bit rate, throughput and the transmission delay. The computer networking and the packet switched networks, with the quality of service refers to the traffic prioritization. OPNET model works on the traffic classifier with performance analysis is through the voice queue pf_fifo, video and best effort queue. (lai et al., 2016). The mixed queue is set with the processor that pull the incoming packets from the mixed queue. The identification is for the respective queues along with the exponential terms with mean inter arrival of 10 seconds and payload mean value of 50 bytes. 

OPNET simulator works on the simulation of the behaviour and the performance where the simulation is mainly for testing the changes with the effect of the analysis and the reliability pattern. The associated forms are based on the viable options to make the choice of building and then modifying the performance based on the network standards. The simulation has been performed using Network Simulation tool OPNET, which is an open source windows based simulation tool. The work has been based on the high level language using the .NED files. The simulation has been through the serial communication and the real time communication that has been carried on the browser. OPNET is a discrete event simulator. It has C based simulation library. (Sharma et al., 2016). It has a nice framework built. OPNET have so far been the best simulation software for roadmaps, which we have used. This is because, it has a nice library support for roadmap simulations and it has a GUI based simulation editor, in which the simulation environment (roadmap) can be created in form of a .NED file. The INET framework of OPNET has been used in the simulation. It supports roadmap simulations, along with other networking protocols like UDP, TCP, IP and wireless network simulations. (David et al., 2016).

Through the proper networking protocols, the analysis is based on the time based simulation and the discrete event based simulation. The network simulation works on the modelling techniques that are even analytics to work on the hop-by-hope single system which lose the accuracy. The Discrete event simulation is a largely typical based format with packet-by-packet set to form the activities of the network that are predicted. OPNET works on the networking and the planning of operations in effective manner where the automation process is mainly through the network diagramming. (Guo et al., 2016). The services are based on the research with the commercial notification that the network modelling is set for. The OPNET works on the support mainly by the object oriented and the modelling analysis where the discrete event simulation has been involved with the hybrid simulation techniques and the analytical solutions. The support is distributed through system information that leads to provide an open interface for all the different object files. This will also improve the protocols and the other technologies for a better development of the environment. The modeller is set with the accelerating research and development for properly analysing about the designing patterns and the networks. For this, the GUI is based on working towards the discrete events and with the time-clocked simulation. The iterative progression of the time slots help in executing the system with iterating all the time slots with the events that are set for a particular limit. (Kalamani et al., 2014). The implementation of the OPNET works on the standalone, floating access licence mainly from the remote server and the server licence from the computer. This is based on working towards the floating standards with the IP address mainly referring to the OPNE which is set for the server predefined listening port. The variables are set for the access of all the relevant files which will help in accessing the applications with different paths of the files. The OPNET standards work on the command line without any setting that could be found for the application research. The command is set for finding the dependent files with the modules to properly check and configure the C++ environment variables as well as allowing the OPNET Modeller for the functioning process in an effective manner. For this, the configuration is also done through setting up the Visual Studio environment variables which is mainly for the different command line sessions. The files are set to work on user preferences where the use logs into the system with setting up the environment variables and other commands. The OPNET simulator works on the different compilation and the linking options where the compiler could easily be used for the compilation of the source code into the object code. This will also help in the operating system to easily load into the executable memory which could easily be loaded for the execution purpose. With this, the control compiling and the linking process could be set in a customized manner where there is a debug of information with the development of the simulation kernel preference. It also models the optimization without any debug of the information. (Bian et al., 2015). The setup is based on handling the customized compilation and then setting a link for a proper compiler option. In OPNET, there is a possibility to follow the process where there is a pre-configured object oriented code simulation which is relevant to the facilities and the other dependent models for the simulation. The processes are based on the management of project with the interface that is set for the File-Manage Model Files. The themes could easily be set through the modeller preferences where linking and compilation is through memory management and licencing. The preferences are mainly about the search and how to handle the project files in effective manner through searching for a backup material. At the time of simulation, OPNET also works on forcing the machines to beep depending upon the requirements, with writing process model code that has been set for the simulation data for analysis. OPNET works on creation and the editing of the network models with managing project scenarios in an effective manner and with verifying the link connectivity. The records are set with the packet flow animation process and with the movement of the nodes for the subnet. OPNET works on the model of network, node and process which is set to handle the objects as sub networks. (Akhter et al., 2013).

Simulation of Behavior and Performance with OPNET

We have solved the speed issue by running a cycle of continuous broadcast, at an interval, which can have been simulated using OPNET. For the project, there is a need to create it, work on the baseline scenario, import or create the topology and then import or create the traffic. It is important to choose the results and the reports can easily be collected from this with duplicate scenario. The comparison of the results is working on the three-tiered OPNET where the node model specifies the object which are in the network domain. The process model is able to specify the node domain where the nodes, links and the subnets are set for the network devices and the group of devices. (Zhang et al., 2016). The links are mainly to represent the point-to-point and the bus links which are for the assistance of the user in the quick location to correct the nodes and the links. The node domains are based on the basic building blocks which also include the processor and the transceivers. The interfaces are between the modules and the packet streams through the static wires where the entire processing of the model consists of the state transition diagrams. The blocks are for the C code where the kernel procedures have been set with the state variables and the temporary variable standards. The instance for the process model is for the creation of child process which response to the interrupts. There have been different outputs for the vectors, scalars and the animations with the packet flows and node movements. The objects have a pre-defined statistic where the throughput, bit received and the forwarded bits are set depending upon how the events are simulated. (Guo et al., 2016). The OPNET simulation works on the event driven patterns where there is a time advancement that will occur when the event occurs. The major focus is on the accuracy of the results by the sampling resolution. The simulation is found to be inefficient when there is nothing for the longer time. The event list concepts are for sharing the simulation time, clock with the events that are scheduled in the timely order. The forced state is the process with enter and that exists with the transition that is traversed to the next state. The simulation is set with the termination in four ways where:

  1. The event has been listed and is emptied.
  2. The simulation attribute works on the duration that has been expired.
  3. The process calls are for the termination where one can use KP op_sim_end()
  4. There is occurrence of a fatal error.

With the advancement of time, the simulation works on the event where the time is processed and worked on from the list of events. There has been simulation that occurs at the execution with no time elapse at the transition between the states. (Zhang et al., 2016). The process model also works on the unforced state so that there is easy advancement and avoidance of the endless looping. (Sharma et al., 2016).

Discrete Event Simulation in OPNET

OPNET simulator works on the tools to simulate the behaviour with performance of different types that are set in the network. The simulation is based on power and versatility which makes it possible for the OSI model set with all the physical parameters. The standards are set with the knowledge to properly understand about the scope of the simulation tool with the focus on how the OPNET MODELER is able to work on the programing simulation environment. The implementation is through the advanced networks and mainly deals with all the important entities that are set for the production of the big networks for the design validation process. The network implementation through OPENT will help in setting a better infrastructure where the networks are mainly defined to be interconnected with the router. The major purpose is related to the support with initial topology that has been set with network enlargement and the simulation redo process, comparing it with the results in effective manner. with the designing, there are server loads and the delay graphic which are set to analyse the work station structure that are set on OSI model. The setup is based on enlargement with lower level designing process. The infinite queue is for the FIFO that is set and known to be M/M/1. The packets tend to arrive at the location which tend to follow with the distribution process with constant rate of the buffer. The designing is also based on linking the data flow, set from one source to the other. The simulation is with the DES simulation where the collection of data could be delayed mainly due to the buffer or the size of the queue. (Alkhathami et al., 2017). The technology has been set to analyse about network topology and the routing protocol which is configured to go through the traffic. The prediction and the validation of the networks in the OPNET is mainly set through, which is useful for handling the devices and the flow of traffic in effective manner. This also leads to change the functions with implementing the change to completely predict about the verification of the device. OPNET works on the products of the network and the implementation that has been set with complex scenarios.

The nodal level output is based on the simulation operations at the packet level that has been built for the fixed networks. It also contain the different number of memory models which are for the network hardware and the possibilities. The standards are set to provide a wider range of the network through the simulation with analysis based on the end user tool. The network domain is set with the OPNET process which consist of the communication with other packet streams. This is set to create a better supply for the different node models. The implementation is based on working for the process editor and the functionalities, where OPNET also allow the modeller with the unformatted and the formatted forms. One can easily work on the packet objects to invoke all the unformatted forms of API. This will also help in creating a proper size with the size of each field set in a formatted packet. The setup is also based on working over the models in the real world packet setup with the use of model that has been for the encapsulated packet. (Chen et al., 2014). There are nodal levels which are for the creation of simple wireless networks and to handle the functional element in a proper manner.

Compilation and Linking Options in OPNET

The node models are set with the requests which are for the other variable to response. This includes the sending and the requesting based on acknowledging the details by sending the echo to the other node. After proper processing, the node is able to send the response to the video with a request. The distinguishing factor is mainly to use the separate inputs and the output buffers which could be for the request and the response packets, where a possible deadlock can come. Hence, for this, there are certain sources with the estimation before the buffers are split into the request and the buffer for the response could also be disregarded. The model is set with the nodes where there are sub modules and the src, dest stat to handle the value which is scheduled in a proper manner. The modules are also for the input buffer for accepting the packet data and it is then forwarded for the inputting of the buffer with the positive echo that is returned for the stripper. The model also includes the value in the positive echo which could easily be done in a detailed format through bypassing the FIFO model. The input buffer is set when the packet is serviced and it is able to hold the packet for the simulation of the service time with the FIFO to enter into the request and the respond queue. The output manager tends to forward the packet which is then inserted into the active bugger. (Huh et al., 2015). The output manager is able to work on the request and the response depending upon the interruptions with the mux module, which is chosen for making the best choice for the polls with incoming statistics. The decisions could easily be made for the output manager where in the output buffer could easily forward the packet from the selected buffer to the mux. The interruption is for the module which receives the packet where the bypass FIFO is empty and the output buffer is not empty. Hence, at the end one could find the FIFO which is non-empty where the node enters into the stage of recovery set with all the upcoming transmissions. (Aneiba et al., 2016).

The queue is important for the networking to line up in a sequential form with the changing header or the trailer. This has been set with the defined packet processing of the algorithm with the queues to handle the data packet when there is a need to transfer and the trailer is set by adding new data packets.

Node Model and Process Model in OPNET

In the queue, there have been only two major operations which are important for the enqueue and the dequeue process. The enqueue process is the insertion of the item into the queue and dequeue is for the removal of the front item where there is easy demonstration in the FIFO process. The difference between them is the removing.

M/M/1 is the queue which is set for the Markovian process or the arrival process. This has been set with the random variable for the number of the arrivals at a particular time.

G/M/1: in this, there have been queue length in the system where there have been times for the inter-arrival patterns. Here, the distribution is based on the service times with the exponential distribution. The system is Kendall notation.

M/D/1: The queue length has been in the system with a single server where the arrivals are determined through the Poisson process. The job service times are fixed with the models set with the server in the M/D/c queue. The arrivals are set with the state space which corresponds to the number of the system entities. (Ye et al., 2014).

D/D/1: The queue length is with the exception in this where the system is set with no randomness.

The active queue is the intelligent drop for the network packets which are set in the buffer associated to the NIC. The passive queue works on the Quality of Service (QoS).

The main parameters which control the traffic generation by traffic sources in a network simulator are:

Time

Number of cars per unit time

Road map/distance

Frequency of occurrence of new cars

Maximum number of allowed vehicle

The automation works on the process which handles the computer network traffic. The important is based on the parameters to the number of different traffic class. (Sadiwala et al., 2015) 

Conclusion

The work has been done on the throughput and analysing the traffic type which has been computed at the processor to the designed module. The standards are set in the network for the proper simulation and then time formulation. There have been queues in the report which are important for the communication and networking. The stacks are set with the passive and active queues where the traffic classifier are important. (Aneiba et al., 2016). OPNET works on the network development where the communication is based on the graphical user interface mainly to enable the developing models from the actual world network. The network planning is for the proper analysis of the performance and the problems which are prior to the implementation. OPNET has been significant simulation with the ability to modify the memory of the utilization at the time of simulation. It also works on the execution and the ability to modify the network parameters which see that the effect of these changes is found in immediate.

Reference

Lai, Y. H. R., Chu, J. Y., & Petrick, J. F. (2016). Examining the relationships between perceived value, service quality, satisfaction, and willingness to revisit a theme park.

Sharma, A., & Dhaliwal, D. K. (2016). Simulation Based Analysis of Jamming Attack in OLSR, GRP, TORA and Improvement with PCF in TORA using OPNET tool.

Aneiba, A., & Chibelushi, C. C. (2016). OPNET-Based Performance Analysis of a Multi-agent Architecture for Managing the Mobile Content Delivery Process. In Information Science and Applications (ICISA) 2016 (pp. 127-137). Springer Singapore.

David, N., Anyakoha, C., & Agbo, H. (2016). OPNET based simulation for Rural Educational ICT Connectivity. International Journal of Scientific & Engineering Research, 7(4), 1499-1504.

Zhang, Q. L., He, R. X., Lin, B., Li, S., & Wang, Y. (2016). OPNET-based modeling and simulations on dynamic bandwidth allocation algorithms in long-reach passive optical networks. In Wireless Communication and Sensor Network: Proceedings of the International Conference on Wireless Communication and Sensor Network (WCSN 2015) (pp. 908-916).

Kumar, S., Islam, S., Das, N., & Gardner, B. (2016). NCIT Enabled OPNET Based Design of a Digital Substation for IEC 61850-9-2 Implementation. IEEE Transactions on Power Delivery.

Guo, Y. L., Pan, Y., & Cai, L. (2016, June). OPNET-based analysis of MTU impact on application performance. In Computer and Information Science (ICIS), 2016 IEEE/ACIS 15th International Conference on (pp. 1-5). IEEE.

Kalamani, P., Kumar, M. V., Chithambarathanu, M., & Thomas, R. (2014). Comparison of RIP, EIGRP, OSPF, IGRP Routing Protocols in Wireless Local Area Network (WLAN) by using OPNET Simulator tool-A Practical Approach. IOSR Journal of Computer Engineering (IOSR-JCE).

Bian, D., Kuzlu, M., Pipattanasomporn, M., Rahman, S., & Wu, Y. (2015, July). Real-time co-simulation platform using OPAL-RT and OPNET for analyzing smart grid performance. In Power & Energy Society General Meeting, 2015 IEEE (pp. 1-5). IEEE.

Akhter, S., Myers, J., Bowen, C., Ferzetti, S., Belko, P., & Hnatyshin, V. (2013). Modeling DDoS Attacks with IP Spoofing and Hop-Count Defense Measure Using OPNET Modeler. In Proc. of International Conference OPNETWORK.

Sharma, A., & Dhaliwal, D. K. (2016). Simulation Based Analysis of Jamming Attack in OLSR, GRP, TORA and Improvement with PCF in TORA using OPNET tool.

Alkhathami, M., Alazzawi, L., & Elkateeb, A. (2017, January). Large scale border security systems modeling and simulation with OPNET. In Computing and Communication Workshop and Conference (CCWC), 2017 IEEE 7th Annual (pp. 1-8). IEEE.

Chen, B., Butler-Purry, K. L., Goulart, A., & Kundur, D. (2014, September). Implementing a real-time cyber-physical system test bed in RTDS and OPNET. In North American Power Symposium (NAPS), 2014 (pp. 1-6). IEEE.

Huh, J. H., & Seo, K. (2015). RUDP design and implementation using OPNET simulation. In Computer science and its applications (pp. 913-919). Springer Berlin Heidelberg.

Aneiba, A., & Chibelushi, C. C. (2016). OPNET-Based Performance Analysis of a Multi-agent Architecture for Managing the Mobile Content Delivery Process. In Information Science and Applications (ICISA) 2016 (pp. 127-137). Springer Singapore.

Ye, X., Wen, F., Ang, S. P., & Salam, M. A. (2014, December). OPNET-based performance analysis of the communication network in a charging station of electric vehicles. In Power and Energy Engineering Conference (APPEEC), 2014 IEEE PES Asia-Pacific (pp. 1-6). IEEE.

Sadiwala, R. C., & Saxena, M. (2015). Transformation and Analysis of Wire line Networks to Wireless Networks Using OPNET Simulator. International Journal of Broadband Cellular Communication, 1(1), 12-27.

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