Jože Mohorko

Mathematical model of IRIS replication mechanism for the simulation of tactical networks

The Multilateral Interoperability Programme (MIP) was established to promote more successful and better harmonized operational functions for international peace-keeping forces. The C2IEDM/JC3IEDM (Command and Control Information Exchange Data Model) ensures the interconnection of Command and Control Information Systems (C2ISs) throughout all levels, from the corps down to the lower ranks. The usability of C2ISs highly correlates with the capacities of data information carriers, and the need is growing for greater capacity and reliability of transmission media and cryptographic message security. Simulation of tactical networks is an important task in planning military missions. Such methodologies assure a higher probability of success during critical tactical operations. This article focuses on a new radio network modeling method for the C2IS, which is verified by the OPNET simulation environment. This modeling method can be used in tactical radio network planning and optimization processes.

Modeling of captured network traffic by the mimic defragmentation process

Over recent years, in order to assist the evaluation, construction, and upgrade of communication networks, the need for the simulation of complex communication networks has increased. Traffic modeling has had a very large impact on network simulation reliability, which is usually statistically described for simulation purposes. Most often, the network traffic analysis is based on the captured packets. However, modeling of network traffic is usually described by statistics of data sources, from higher layers of a Transmission Control Protocol/Internet Protocol (TCP/IP) model. For these reasons, we have developed a method that allows distribution parameter estimation of the data-source process from captured packets. This method is based on the algorithm, which mimics defragmentation as opposite to the TCP/IP fragmentation and encapsulation processes. The proposed method achieves an accurate description of network traffic.

MIMO simulator of call server input lines occupancy

This paper presents and solves the problems of modeling and designing the necessary capacity and the adequate capacity of accepting input connections serving the calls into the system. The main aim of the research work is finding the optimum number of input server connections while minimizing the number of rejected requests according to a specific maximum number of expected calls in a specific time-interval, i.e. at peak-hour. With the results obtained we wish to model and optimize the planning and the dimensioning of the processing server as well as reduce the costs of this, since hiring an input line actually presents quite a substantial cost. Therefore it is necessary to first determine how many input connections are needed to serve a certain quota of users at a specific moment by using the methods of statistical modeling. On the basis of obtained results we can then assess whether a certain segment has too many or not enough input connections. The objective of the presented multiple-input and multiple-output (MIMO) simulator is to raise the level and the quality of service and at the same time lower the costs of hiring input connections. This paper presents the key segments composing the call and server system (ordinary, lamer and dummy caller model, statistical Gaussian curve of calls distribution, mechanisms of accepting and rejecting calls, management of input connections capacity, random call triggering, etc.). The above-mentioned segments represent the models and the sub-models of the simulator. They have been derived using the methods of statistical modeling. The optimum solution can be found manually or automatically using the method of automation of simulation runs and incrementing/decrementing the parameter of the number of input connections into the system. Searching the optimum number of input connections manually is an entirely empirical method, where the user manually changes the mentioned parameter, and is looking for a scenario in which the result of the simulator regarding the number of rejected calls is minimal. With an automatic search the simulator automatically generates the number of runs with incrementing and decrementing the mentioned parameter in each, and thus automatically finds the optimum solution. This paper also presents an automatic analysis of simulation runs and a statistical final report, which includes a conclusion on the results obtained in different scenarios.

Limitations of a Mapping Algorithm with Fragmentation Mimics (MAFM) when modeling statistical data sources based on measured packet network traffic

Knowing the estimation of a statistical processs parameters for measured network traffic is very important as it can then be further used for the statistical analyses and modeling of network traffic in simulation tools. It is for this reason that different estimation methods are proposed that allow estimations of the statistical processes of network traffic. One of them is our own histograms comparison (EMHC) based method that can be used to estimate statistical data-length process parameters from measured packet traffic. The main part of EMHC method is Mapping Algorithm with Fragmentation Mimics (MAFM).The MAFM algorithm allows the estimation of a theoretical packet-size histogram for different distributions of the data-length process. In this paper describes in detail the limitations of a developed algorithm, which are correlates with the long-range dependence of data-length distribution. It is shown that a developed MAFM algorithm has limited usability for distribution types which do not posses the finite value of an expected value. In order to improve the robustness for such types of distribution, the new parameter ULS (Upper Limit of Summa) is involved in the original MAFM algorithm. The ULS parameter limits the tail of the distribution. By assuming a finite ULS value, the MAFM algorithm can now be used for all distributions of the data-length process, as well as for distributions without a defined expected value, such as Pareto. The presented analytical results have been confirmed by experiments through the use of the simulation tool.

Modeling of statistical data sources based on measured network traffic

In the process of network traffic modeling, for simulation purposes, there is often a need for statistical description of traffic data sources. Usually, the network traffic is measured by capturing packets at a physical level. Normally, the estimation of statistical description of traffic data sources cannot be derived directly from such captured packets traffic. For that reason, we have researched for simpler solutions, which are based on the estimation of statistical processes of traffic data sources from the measured packet network traffic. We have developed the estimation methods, which allow the estimation of suitable probability distribution functions and their parameters of stochastic processes of traffic data sources. Statistical distributions of network traffic processes, such as data lengths process and data inter-arrival time, are important since they can be used for modeling of network traffic in simulation tools. For that reason, the estimation method is firstly developed, which mimics the defragmentation process. This method allows an estimation of distributions of data source network traffic processes and their parameters for captured packet traffic. During further testing, this method shows some limitations, especially for the process of data lengths. For that reason, we have developed a new estimation method with the approach described in this paper in further detail. In the new estimation method, which is called estimation method based on histogram comparison (EMHC), we use the opposite concept where distribution of data lengths is transformed by a developed analytical model to a packet size’s histogram. The latter is further compared to a packet size histogram of captured packet traffic. The optimization method is used to find such distribution parameters of the data length process that cause minimal discrepancies between the histogram of captured packets and the estimated packet size histogram. To estimate the discrepancy between two histograms, a well-known χ2 test is used, which is modified by a weighting function that considers, beside packet frequencies, the packet lengths as well. The proposed algorithm and method are confirmed through validations and experiments in a simulation tool.

Modeling and Simulating the Self-Similar Network Traffic in Simulation Tool

Telecommunication networks are growing very fast. The user’s needs, in regards to new services and applications that have a higher bandwidth requirement, are becoming bigger every day. A telecommunication network requires early design, planning, maintenance, continuous development and updating, as demand increases. In that respect we are forced to incessantly evaluate the telecommunication network’s efficiency by utilizing methods such as measurement, analysis modeling and simulations of these networks.

Location and visualization of the communication problems in a simulated Slovenian Armed Forces tactical radio network

The article presents a concept of design, using the methods of simulation results, automatic analysis, and taking into account expert knowledge, and visualization of communication problems in the developed Tactical Player. The main emphasis is on the segment of simulation results evaluation on the basis of fuzzy sets, from which we have developed rules, the combination of which is used for evaluation of the quality of communication parameters between tactical radio stations. A special note should also be taken of the concept of modeling a tactical radio network and its characteristics, the mode of communication between radio stations, hierarchic organization, the problems of manual analysis of simulation results, etc. We present our solution for automatic analysis and the solution for visualization of problematic segments in the course of communication. The reader is acquainted with the problems of wireless communications and the key parameters influencing the connection between communicating entities, such as radio visibility, message transfer success, packet loss, deterioration of the signal–noise relation, etc. Because visualization of problematic time frames of the simulated communication on a virtual simulation field directly depends on the automatic analysis precision, we also used mathematical procedures (probability theory and possibility theory) as the basis of the fuzzy logic used. For a better understanding of the modeled prototype’s functioning, we also include a block scheme in the form of a process scheme, on the basis of which we can show the segments that are new and are a scientific contribution in the field of simulation techniques.

Automatic control and adjustment of TV picture geometry

Abstract The foundation of computer vision system for testing, controlling and adjusting of the TV sets is a mathematical model of distortion of the TV picture. Adequate accurate model description parameters are given by polynomial of order eight and knowledge based nonlinear, cross coupled relationships between command variables for adjusting of the TV sets and coefficients of polynomial.