Joze Mohorko

A new goodness of fit test for histograms regarding network traffic packet size process

Contemporary communication is becoming more and more complex and extensive. Network planners very often use simulations tools for reducing the costs of planning, constructions, and maintenances. Modeling network traffic is also a very important challenge regarding simulation tools, especially the modeling of measured traffic as to which would be the best approximation of measured traffic in real network. This is possible to ensure using the accurate descriptions of two random processes, both of which define network traffic. These two random processes are packet size process and inter-arrival time. In stochastic modeling both of these processes are modeled using probability distributions. The parameters of these distributions are estimated in an empirical manner with the help of histograms regarding measured traffic processes. Any accuracy regarding suitable distribution between distribution and histogram can be evaluated using different tests, such as Kolmogorov-Smirnov or Chi-square. However, during the measurements and modeling of measured network traffic these tests show one weakness in the case of trying to model network traffic, in regard to the best approximation of measured traffic in bit and packet-rates at the same time. So we have developed a new and better goodness of fit test of network traffic, which considers the number of packets and also the packetpsilas size. Using simulations we show, that the use of this new more suitable test leads to better choice regarding distribution when describing a packet size process, which than consequently, also lead to smaller discrepancies between measured and simulated traffic in bit and packet-rates.

Modeling methods in OPNET simulations of Tactical Command and Control Information Systems

Slovenia is a member of MIP (multilateral interoperability programme), the task of which is to provide interpretations of national C2IS systems for successfully harmonizing joint action by international military peacekeeping forces. Interpretability within MIP is carried-out by a unified model based on controlled data replication between the databases of C2IS systems. Systematics IRIS replication mechanism software (IRM) is used for data replication. This paper presents methods of measuring and analyzing traffic that causes IRM. We designed an OPNET model on the basis of the analyzed results that would be suitable for the purposes of tactical radio network simulation.

Packet size process modeling of measured self-similar network traffic with defragmentation method

Analysis and modeling of telecommunication networks by simulations has become one of the main tools in the process of telecommunication-networkspsila planning and upgrading. Knowledge regarding the statistical modeling of network traffic is very important. Here we tend towards modeled network traffic which would be the best possible approximation of the measured traffic. Throughout our research in the field of self-similar network traffic we have faced problem of statistically describing the packet-size process. We have noticed that small discrepancies between measured histograms and estimated probability density functions, as used in traffic generator models, lead to large discrepancy between measured and modeled network traffics. In this research we tried to estimate the probability density function of a measured histogram for process-packet size, in such way that would decrease these discrepancies. For this purpose, we have developed a novel method of modeling network traffic, which is based on the defragmentation of measured traffic. Using this defragmentation method, we can estimate parameters of filespsila size process, from captured packets and use these statistical parameters for traffic generation, via the OPNET simulation tool. From these simulations, we can show that this newly-developed method decreases discrepancy between packet size process histograms of measured and simulated network traffics. This consequently leads to a decrease in discrepancy between measured and simulated network traffics.

Real time “system-in-the-loop” simulation of tactical networks

Military mission success probability is closely related to careful planning of communication infrastructures for Command and Control Information Systems (C2IS). Over recent years, the designers of tactical networks have realized more and more need for using simulation tools in the process of designing networks with optimal performances, in regard to terrain conditions. One of the most demanding simulation problems is the modeling of protocols and devices; especially on the application layer, because the credibility of simulation results mainly depends on the quality of modeling. A new branch of communications network simulations has appeared for resolving these kinds of problems the - simulations with real communication devices in the simulation loop. Such simulations initiate real-time into the simulation process. The results of our research are aimed at simulation methodology. Using this system, military command personnel, can perform realistic training on the real C2IS equipment connected to the simulation tool, by modeled wireless links over a virtual terrain. In our research work, we used the OPNET Modeler simulation tool, with additional modules.

Result visualization in tactical network simulations

A lot of expert knowledge for correct simulation realization and result interpretation is needed in tactical network simulations using an OPNET Modeler. So we have built a system, which would simplify the processes of simulation preparation and the interpretation of simulation results. The system for tactical network simulation has been designed as three assisting program modules. TPGEN takes care of simulation parameters preparation, Expert system automatically analyzes simulation results and the Tactical Player is for user-friendly visualization and examination of analyzed data. We have successfully realized visualization of analyzed data with the usage of a Tactical Player, capable of interpreting simulation and expert systempsilas results in text or 3D graphical formats, with or without simultaneous usage of the OPNET Modeler.

Real video stream transmission over simulated wireless link

The most difficult task when using simulation tools for communication networks and protocols is usually represented by the modeling of applications and their protocols for different networkspsila technologies. For this reason, the need for simulation tools appeared, which could connect real communication applications and networks with simulated networks. This paper presents some simulation results regarding real-time simulations, which were done in the context of a military project about the modeling of Command and Control Information Systems. A new OPNET Modeler module System-in-the-Loop was used, which allows for communication between real and simulated devices and networks, and represents a new simulation approach. The test network we built using these tools, where we connected computer equipment producing real-time video stream with a simulated mobile wireless 802.11g network on a virtual terrain.

Fast algorithm for pyramid vector quantization

This paper presents an efficient implementation of a pyramid vector quantization coding/decoding algorithm developed by Filip and Ruf (see Proc. IEEE Conf. GLOBECOM, Orlando, FL, USA, p.240-4, 1992), where the original classical calculation of pyramid numbers V/sub L,K/ is replaced by a sliding calculation. The sliding calculation allows movement in any direction of a lattice so that the calculation of V/sub L,K/ in each algorithm iteration can be continued from the previous pyramid number. These properties can, under certain conditions, significantly (up to 25 times) accelerate the coding/decoding process. The condition under which the sliding calculation is more effective than the original one is also presented. The simulation results confirm the expected improvement over the original algorithm.

A system for the expert analysis of tactical networks’ performances

The simulation of tactical networks is an important task in the process of military missions planning. Such methodologies assure a higher probability of success for tactically critical operations on military fields. The manual analysis of simulation results is a very time-consuming task and requires expert knowledge to correctly interpret these results. This paper briefly defines those concepts of an expert system also used in the design of our system for automatic expert analysis regarding those simulations results obtained by an OPNET modeler. It presents some analyses algorithms which we have developed for tactical network evaluation. The more important parameters that evaluate tactical networks are: transmitter bandwidth utilization, traffic delays, message completion rates and radio visibility. The functionalities and implementation of a developed expert system are also described in the context of the whole system for simulating tactical networks.

Mathematical analysis of routing, based on circular graphs

Routing is a problem domain with an infinite number of end-solutions. One possible approach is to solve such problems using of graph theory. This paper presents a mathematical analysis for a routing problem, based on circular graphs, where the focus is on searching for the shortest path on a circular graph. The theoretical section will be argued by an example where we look for the fastest path and possible walks within specified circular graph.

Expert System for Automatic Analysis of Results of Network Simulation

The simulation of communication networks is an important task in the process of network planning and optimization processes. Such methodologies assure a higher probability for networks to operate successfully under different critical conditions, which are difficult or unpractical to be tested in the real networks. Typical applications of such simulations are the simulation of military tactical radio networks. The manual analyses of network simulation results, is a very time-consuming task and requires expert knowledge to correctly interpret such results. This is a good motivation to develop the system for automatic analysis with expert knowledge, which will ease the process of mission planning and training. For such needs, we have developed the simulation methodology and tools, supported by the expert system, which are going to be presented in detail within this chapter. During this chapter, we will briefly introduce expert systems (further ES), Command and Control Information Systems used in NATO and known solutions to simulate such systems. The ES is defined as an intelligent computer program with a certain level of expert knowledge, which using procedures to solve exactly specified problems. All definitions for expert systems, in many books, are quite similar, and they describe the way such system includes a rigid range of expert (specialized) knowledge or research domain. Within this area, it is capable of creating intelligent decisions. This is some kind of imitation, where a system tries to capture behavior of skills. Using the acquired knowledge; a system can analyze input/output information, solve problems, and utilize utensil decisions within the problem domain. From this point of view, these systems cannot solve all kinds of problems, but they can solve well-known and deduced problems. It is stated in one of the references that expert systems are based on knowledge (Hart, 1998, pg. 7), respectively on an information handler base. Classification by Sauter places an expert system on the right side of the straight line, where we can find systems, which handle information. Expert systems are closely related to artificial intelligence methods. As a rule, they share quality and quantity information, probability theory, fuzzy set theory, and a number of arithmetic and logic rules, based on heuristic expectations.