Research topics - Department of IT Systems and Networks

Queuing methods in reliability theory, computer and communication systems

Using the methods of queueing theory our aim is to investigate the performance measures of complex info-communication systems including among others wireless networks, sensor networks, cognitive radio networks by the help of analytical, numerical approaches combined with tool supported analysis. The research carried out by the group is focused on the so-called finite-source queueing systems. Its origin dates back to the machine interference problem, sometimes called machine-repairman model. It was later applied for the performance modelling of time-shared terminal systems and repairable complex systems, just to mention some.

Investigating the throughput performance of multipath communication

The current Internet communication environment allows only a single path for data transmission in a communication session. The single path assumption is quite acceptable for systems, which use a single connection interface, or a “single exit point” to the Internet. On the other hand, a lot of currently used devices have got factory built-in multiple network interfaces: RJ-45 for the wired network, RF interface for the Wi-Fi wireless network connection, and mobile phone data transfer connection interface (e.g. 3G, HSDPA or LTE). The single path communication technology is not able to use the advantages of the multiple interfaces. The communication performance (e.g. throughput) could be highly improved if the networking environment would be able to support the usage of multiple paths for a communication session.

Congestion management

At the beginning computer networks and the Internet were designed mainly for data transfer such as FTP and email, where delay was considered to be unimportant. In most cases the delivery service was effective, and the TCP protocol dealt with data losses. As the multimedia applications became popular (voice transfer, video conferences), separate telephone and video communication networks were set up. Nowadays, office and company networks are transformed into one converged network, in which the same network infrastructure is used to ensure all the requested services. Although converged networks have many advantages, there are some disadvantages too, namely the competition for network resources (buffers of routers), which leads to congestion. Congestion is a state, when in (a part of) the network are too many packets which causes packet delay and loss that degrades performance. Delay in delivering the packets, jitter, loss of packets are consequences of congestion. Different applications show different sensitivity to these issues. For example, FTP is not impacted by delay and jitter, whereas the multimedia applications (video, voice) are very sensitive to them and the loss of packets too. Therefore, the analysis of the algorithms for congestion management is a hot research area.

Modeling of complex networks

The properties of many-particle systems cannot be analyzed in analytical way, therefore one have to apply the tools of statistical physics. Complex networks have special characteristics: scale-free and ’small-world’ property, etc. There are several systems in our natural, technical and sociological environment, which based on complex networks (i.e. social-, transport-, computer-, cooperation- and metabolic networks). The topological modeling of them and computer simulation of their processes are important and useful in science. Our results belong to fracture and fragmentation of solid materials and clustered or dying social networks.

Computer simulation of spreading processes

In this topic we investigate diffusion phenomena that is present in many fields of science. In the first place we use computer simulations and analytical calculations during our work. The observed phenomenon may be information spreading on a social network, the spreading of a new technology, or even an information packet on a computer network. in our work usually we use discrete time and several different network topologies. Our results are published in international journals and at high noted conferences.

Development of Ultrasound-CT

We have studied different experimental UHCT configurations the necessary basic instrumentation (uC, NI PXI, FPGA controlled), algorithms and software environments resulting sufficient experience for further work towards using experimental arrangements with a higher number of 3D arranged transmitter-receiver pairs in fluid as a coupling medium.

Development of Distributed Sensor Network for meteorological observations and numerical weather Prediction Calculations

The prediction of weather generally means the solution of differential equations on the base of the measured initial conditions where the data of close and distant neighboring points are used for the calculations. It requires the maintenance of expensive weather stations and supercomputers. However, if weather stations are not only capable of measuring but can also communicate with each other, then these smart sensors can also be applied to run forecasting calculations. This applies the highest possible level of parallelization without the collection of measured data into one place. Furthermore, if more nodes are involved, the result becomes more accurate, but the computing power required from one node does not increase. Our Distributed Sensor Network for meteorological sensing and numerical weather Prediction Calculations (DSN-PC) can be applied in several different areas where sensing and numerical calculations, even the solution of differential equations, are needed.

Implementation of artificial neural networks in field-programmable gate arrays

The research aim is to design hardware implemented artificial neural networks (ANN) using reconfigurable hardware (FPGAs). For hardware implementation we can choose between HDL description of the NN, high level synthesis tools (HLS) and a new method that I have developed using the System Generator tool by Xilinx. This method allows the easy generation of hardware description Language (HDL) code from a system representation in Simulink. This HDL design can be synthesized for implementation in the Xilinx family of FPGA devices. In this way is possible to create “application specific neural networks” in an easy and fast time to market way. We have implemented and trained in many different ways Feed-Forward ANN and also competitive neural networks. Use case: Application of hardware implemented ANN in activity pattern recognition.

e-Health and Ambient assisted living systems

Our research aims to assist elderly or sick people everyday independent activities using the latest assistive technologies based on Internet of Things. The system consists of three major components: intelligent ambient assisting living system, the health and activity monitoring and recognition system, and an assistive robot providing personal assistance. This is a complex support system, which must have learning and adaptive behavior, and for this reason we plan to use artificial neural networks.

Intelligent embedded systems design and applications

We designed a hardware-software co-design platform based on FPGA, developed for fast prototyping of embedded systems using hardware modules that can be easily connected and “driver” modules that can manage I/O devices and sensors basic behavior. Using neural networks (NN) to add learning capabilities and adaptive behavior is essential for an intelligent system and the use of FPGA is an important feature in terms of their hardware implementation. The designed architecture allows the insertion of intelligent interface based on neural networks created with this type of modules. This platform is based on low cost general purpose FPGA boards without need for hardware design. Among possible applications are intelligent computer peripherals enabling people with any kind of handicap to use computer and communicate, as any kind of industrial or domestic device with embedded and hidden intelligence at user for prosthetic, automotive, “domotic” and automation fields where the trend is to produce easy-to-use devices.

Updated: 2018.01.07.

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