Search

V doktorski disertaciji predstavljamo reševanje problema načrtovanja in planiranja strežnih kapacitet dinamičnih strežnih sistemov s stohastičnimi izbruhi. Skladno z reševanjem omenjenega problema rešujemo tudi problem dinamične rezervacije in redukcije telekomunikacijskih linij. Primarni cilj raziskovalnega dela se navezuje na iskanje optimalnega števila vhodnih telekomunikacijskih linij v Margento strežni sistem mobilnega plačevanja ob minimizaciji števila zavrnjenih transakcijskih zahtev v obdobjih koničnega stohastičnega obremenjevanja. Z iskanjem optimalne rešitve za specifičen scenarij rešujemo še problematiko točne napovedi nabave strojne opreme ter problematiko ekonomsko učinkovitega planiranja. Izhodišče za izpeljavo podmodelov in glavnega modela Margento strežnega sistema nam predstavljajo realni rezultati, ki opisujejo obnašanje v pravem sistemu. Razvita metoda temelji na teoriji funkcij porazdelitev, ki jih kot temeljni matematični element uporabljamo v simulacijskem modelu. V navezi z vključeno optimizacijsko funkcijo, ki deluje v režimu spreminjanja parametra strežnih kapacitet in z ozirom na postavljen prag nam razviti model in optimizacija tvorita predlagano metodo planiranja strežnih kapacitet, katere osnova sta simulacija/emulacija ter matematične funkcije porazdelitev. Z optimizacijo hkrati minimiziramo stroške načrtovanja in dimenzioniranja procesnega centra, strežnega sistema, saj najem vsake vhodne povezave predstavlja dodaten strošek, kot predstavlja dodaten strošek tudi vsaka neizkoriščena telekomunikacijska povezava do strežnega sistema. Razlog za razvoj lastne metode načrtovanja strežnih kapacitet gre iskati v specifičnosti obstoječih rešitev (analitično reševanje, linearne napovedi ipd.), kjer slednje postanejo prekompleksne v primeru stohastičnih obremenitev, velike dinamike pri spremembah obremenitev strežnega sistema, ki jih v regulacijski tehniki pojmujemo kot nihanja v sistemu itd. S predlagano in kasneje predstavljeno metodo smo pokazali še njeno univerzalno uporabnost na področjih procesov in sistemov katerih dogajanje lahko opišemo z uporabo enakih funkcij porazdelitev, kot jih uporabljamo v primeru Margento strežnega sistema. Validacijo metode smo izvedli skladno z realnimi podatki iz realnega sistema, kjer smo število potrebnih telekomunikacijskih povezav dobljenih na osnovi metode primerjali s številom maksimalno hkrati izrabljenih povezav v realnem sistemu (logi). V praksi se lahko pojavita tudi oba robna scenarija, in sicer premalo, oziroma preveč povezav, ki sta nezaželena tako za uporabnike kot tudi za ponudnika določene storitve. S predlagano metodo in lastnim razvitim orodjem (simulatorjem), ki nam predstavlja zgolj pripomoček za analizo različnih scenarijev, želimo dvigniti nivo in kvaliteto storitev ter hkrati iz ekonomskega stališča reducirati in optimirati stroške investicij v nadgradnjo strojne opreme kot tudi najema vhodnih telekomunikacijskih povezav. Optimalno rešitev lahko najdemo z ročnim spreminjanjem parametra strežnih kapacitet (zamudno), oziroma avtomatično, s pomočjo metode avtomatizacije simulacijskih tekov ter avtomatičnega spreminjanja količine strežnih kapacitet. V primeru avtomatičnega iskanja optimuma, razviti simulator, kot orodje in pripomoček, sam generira število simulacijskih tekov in v vsakem izmed njih prilagaja strežno kapaciteto, dokler ne najde ponovljive rešitve v skladu s postavljenim pragom (še sprejemljiv nivo zavrnjenih klicev, transakcij oz. z obzirom na maksimalno še dovoljeno čakalno dobo v čakalni vrsti). V disertaciji podrobno predstavljamo tudi ključne segmente, ki sestavljajo strežni sistem (normalni oz. lažni klic, statistična Gaussova krivulja porazdelitve klicev, mehanizmi sprejemanja in zavračanja klicev, transakcij, upravljanje s kapaciteto vhodnih povezav, naključno proženje klicev itd.) in so hkrati podmodeli predlagane metode. Neposredno primerjavo, s katero pokažemo veljavnost teze na področju planiranja in reševanja že omenjene problema Within the PhD thesis we represent technique how to precisely solve the capacity planning problem for dynamic serving systems which contains stochastic bursts. Corresponding to this, we at the same time also solve dynamic telecommunication lines reservation or reduction problem. The research work primary aim is focused on searching such an optimal serving system capacity solution which will minimize the rejected transaction attempts number under defined limitation during stochastic peak hour load. By searching the optimal capacity solution we also search the proper and economic solution for hardware equipment purchases. For solving all mentioned problems we propose the new capacity planning and optimizing method based on distribution functions (more precisely – based on normal distribution functions). Issue point for deriving new method was real results recorded within the real Margento Mobile Payment serving system. Regarding such results we pick the proper distribution function, which best describes the peak hour load in the Margento serving system. The whole serving system has been split on many subparts, where each of them has been modeled with proper distribution function. The distribution functions are the fundamental part of derived sub models and models which have been used later in simulation procedure. Corresponding to optimization function which operates in incremental/decremental regime and increments or decrements the serving system capacity parameter regarding to achieve rejected transactions attempts ratio under defined level. Models based on distribution functions and optimization loop creates the new proposed planning method usable also for systems which contain bursts, peak hour load intervals etc. With optimization and new planning method we can dimension the processing server as well as reduce the costs of this, since hiring an input line actually presents quite a substantial cost. The reason why we proposed the new planning method can be found in specifics of existing methods. In very complex systems the analytical methods be-came wasteful and computation time to find proper solution, especially if bursts are presented, dramatically increases. All mentioned existing methods are not proper for our needs, because in all cases the unique linearization level is presented to solve complex problems as stochastic bursts and high dynamic changes in serving process are. Such dynamic changes are well known under regulation scientific area as fluc-tuations within the system. With proposed and later presented method we will show their universality of use on such system and process areas, where the happening can be described with the same distribution functions, which are used in case of Margento serving system. Proposed method validation was performed in accordance with real data obtained from real system. The obtained result of our method was then compared with maximal occupied slots at the specific time (peak hour – logs) in real system. The mutual results comparison will show how precise the proposed method is. In practice we can found also both border scenarios, where serving capacity is too small or in opposite case to big. The first scenario is undesirable for end users meanwhile the second one is undesirable for service providers which offer specific services. With proposed method and own developed tool (MIMO Simulator) used as experimental tool for testing different scenarios and proving the method correctness we would like to improve the services quality and from economic aspects reduced and optimized investment costs into hardware equipment and lower the costs of hiring input telecommunication connections. The optimal solution can be found manually (slow approach) or automatically by changing (incrementing/decrementing) the serving capacity. In automatic case the developed simulator generates the number of runs and in each of them increments or decrements the capacity parameter, till then, when repeatedly solution is found, regarding to defined limits (rejected transactions ratio must be under

V širokem razcvetu računalniške industrije in pridobitve velike procesorske moči, so se v različnih industrijskih panogah močno uveljavili izpopolnjeni računalniški sistemi. Le ti so dandanes človeku v veliko pomoč, v nekaterih primerih pa z implementirano umetno inteligenco nadomeščajo človeško bitje. Med sisteme, ki so v pomoč uporabniku, operaterju, delavcu ipd. spadajo ekspertni sistemi z omejenim naborom znanja, in so namenjeni razreševanju problemov iz dobro poznane domene. Znanje za razreševanje problemov je dodeljeno s strani poznavalca (eksperta), ki omenjeno domeno dobro pozna. Sistemi, ki temeljijo na umetni inteligenci se hierarhično gledano nahajajo na višjem nivoju v primerjavi z ekspertnimi sistemi, saj običajno temeljijo na nevronskih mrežah, katere jim omogočajo učenje, le to pa je na nivoju ekspertnih sistemov prepuščeno poznavalcu problemske domene oz. ekspertu. Takšne sisteme najdemo v različnih industrijskih panogah, kjer služijo kot sistemi za: odkrivanje napak na tiskaninah, odkrivanje napak na letalskih in ladijskih sistemih, diagnosticiranje simptomov bolezni v medicini, optimizacijo omrežij… Ideja o izdelavi ekspertnega sistema izhaja iz področja simulacij, kjer bi za določitev posamičnega problema v taktičnem omrežju porabili ogromno dragocenega časa, ob upoštevanju, da moramo za določitev individualnega problema analizirati več simulacijskih statistik hkrati. Da bi takšno proceduro čimbolj poenostavili in pohitrili smo zasnovali ekspertni sistem, ki ga predstavljamo v magistrskem delu, in služi kot pripomoček operaterju pri ocenjevanju in vrednotenju kakovosti zasnovanega taktičnega komunikacijskega omrežja v simulacijskem okolju OPNET. V uvodnem delu magistrske naloge najprej podrobneje predstavimo ekspertne sisteme ter področja na katerih se najpogosteje uporabljajo. Ker smo sami zasnovali ekspertni sistem za ocenjevanje taktičnega omrežja podajamo tudi detajlne opise posameznih gradnikov, ki tvorijo ekspertni sistem odločanja. Narava brezžičnih taktičnih podatkovnih omrežij je takšna, da opazovanih parametrov ni mogoče vedno oceniti z diskretnimi vrednostmi. Opazovani parametri, ki nas zanimajo so: radijska vidljivost, uspešnost prenosa sporočil, zakasnitve v omrežju in zasedenost prenosnih kanalov med posameznimi brezžičnimi entitetami. Tako radijsko vidljivost kot tudi izkoriščenost prenosnih kanalov ocenjujemo z zveznimi pripadnostnimi funkcijami, ki so del mehkih množic, zato smo v ta namen vpeljali teorijo mehkih množic. Iz slednje izhaja tudi teorija verjetnosti/možnosti, ki se uporablja za estimacijo omenjenih parametrov, le ti pa morajo biti po vojaških normativih in zahtevah dovolj natančno določeni. Ekspertni sistem je tesno povezan s simulacijskim orodjem OPNET Modeler, katerega detajlno predstavljamo v magistrskem delu, vključno s predstavitvijo strukture in načina komuniciranja vojaških taktičnih enot na virtualnem terenu. Predstavljena je metoda dostopa do simulacijskega modela EMA, metode sklepanja z mehkimi množicami, delovanje ekspertnega sistema, rezultati analize ekspertnega sistema, poročila, ki jih pripravi ES, ocena skupnega omrežja itd. Today is computer industry in fast grooving phase and offers a lot of computing power and that power is then used at different industry branches where are used high end, and sophisticated computer machines. Computing power is very useful for solving different problems with artificial intelligence or expert knowledge usage. Such machines can replace the human expert on the working place. To systems, which are destined to help the end user, operator, worker etc., belongs expert systems which includes the limited range of expert knowledge. Such expert system solves the problems only from narrow, well known problem domain. Knowledge for expert system is given by an expert engineer, which very well knows the problem domain or problem area. Systems based on artificial intelligence are hierarchically above expert systems because they usually use neural networks for learning. Because of that they can solve problems from different domains meanwhile quality of expert system knowledge depends of experts’ skills. Expert systems (ES in further) and systems based on artificial intelligence (AIS in further) can be found within different industry branches, where they are used for: diagnosing faults on print boards, diagnosing diseases, diagnosing faults on aircrafts and ships etc. The main idea for this master degree thesis issuing from simulation areas, where we spent a lot of precious time for analyzing simulation results to recognize specific problem within the network. Sometimes we have to analyze thousands and more data for each individual statistic, in many cases we have to analyze even more than one graph (statistic) simultaneously. Such procedure is time consumpting. Our solution for this is ES as main support part for diagnose problems within wireless military tactical networks. ES and their main parts, such are user interface, knowledge base, reasoning mechanisms, fuzzy sets for our specific case and theirs implementation are presented in details during this master degree thesis. Such ES is tightly connected with OPNET Modeler simulation tool, because it, over external model access (EMA), get simulation data form Modelers’ simulation output vector (OV). From that aspect ES is an additional module for automatic analysis of simulation results, which could be in future included into OPNET simulation tool. Naturally, statistics of wireless data networks can’t be always estimated as discrete states because observing parameters such are radio visibility, delay, and link utilization must be estimated using specific continuous membership functions defined as fuzzy sets. This is the main reason why we described fuzzy sets. From fuzzy theory hass been also derived probability/possibility theory which is used for estimating membership of individual simulation values in our case. We also introduces reasoning methods, rules, reasoning upon membership functions, reports as output from ES, how it estimates individual node (entity) and how it estimates whole constructed network, how can output reports be viewed etc.

Članek opisuje metode analize in zasnovo sistema za avtomatizirano analizo simulacijskih rezultatov pridobljenih iz orodja za simulacije komunikacijskih omrežij - OPNET modelerja. Pri tem smo se omejili na temeljne gradnike, ki jih sistem mora vsebovati, da ga lahko uvrstimo v razred ekspertnih sistemov. V prvem delu članka smo za vsak gradnik podali temeljit opis. Dodali smo tudi opise mehanizmov mehkih množic, baze znanja in pravil, ki se uporabljajo v procedurah sklepanja in iskanja koncnih rešitev. V drugem delu članka predstavljamo ekspertni sistem, ki smo ga zasnovali za analizo rezultatov simulacij taktičnih radijskih omrežij. V nadaljevanju je opisana funkcionalnost sistema, metode analize, posameznih komunikacijskih parametrov in načini podajanja rezultatov.

Now days the use of mobile communications, applications and mobile data transfer are rapidly increased. The standardization work of GSM-based systems has begun in the 1980s, when the developing of unique radio communications system for Europe, at 900MHz, has started. Since then many modifications have been made in order to fulfill the increasing demand from the operators and cellular users. This paper describes a Universal Mobile Telecommunications Service (UMTS) network and an example of data reception, when web application and voice over internet protocol (VoIP) are used. The UMTS represent third generation (3G), broadband packet based transmission of text, video, digitized voice and multimedia at data rates up to 2 megabits per second (Mbps). The UMTS is intention for consistent set of services to mobile computers and phone users, no matter where they are located in the world. Third generation technology is based on the Global System for Mobile (GSM) communication standard. It is also endorsed by major standards, bodies and manufacturers, as the planned standard for mobile users around the world. Because UMTS is today fully available, computers and phone users can be constantly attached to the internet wherever they are, wherever they travel and as they roam, will have exactly the same set of capabilities. Users will have access through a combination wireless and satellite transmissions. Even today, some places are not fully covered with UMTS, so in that case, users can use multimode devices that switch to the currently available technology, such as GSM 900 and 1800 where UMTS is not yet available. UMTS offers many different applications like: light and heavy web browsing, reading web mail, VoIP quality speech, video conferencing, base access, telnet session, file transfer, file copy, GSM and PCM quality speech, SMS, MMS and so on. We pick out only two applications, and that is light web browsing and VoIP, which are today very popular for most population on the world, because many applications allow user to connect with the whole world at any place and any time. Under the third generation partnership project (3GPP) the third generation of UMTS cellular system was developed. The main parts of this systems are UMTS terrestrial radio access network (UTRAN), based on wide division multiple access (WCDMA) radio technology and GSM/EDGE radio access network (GERAN) based on global system for mobile telecommunications (GSM/enhanced data rates for global evolution (EDGE) radio technology). On the other hand the UMTS can be divided into three major parts: User Equipment (UE) that interfaces with the user and radio interface, UTRAN that handles all radio-related functionality, and the Core Network (CN), which is responsible for switching and routing calls and data connections to external networks. These elements are shown in Fig. 1. In second section the base UMTS elements and their function are presented on Fig. 2 and Fig. 3. Section 3 shortly represents the capabilities of the Opnet Modeler program and describes types of networks, which can be simulated. Section 4 represents the construction of UMTS network in the Opnet Modeler and describes the web application and VoIP. The web browsing is simulated in UMTS network application and object response time and page response time were observed. We located UMTS mobile node with name ,Web2- near UMTS transmitter. If we compare positions for both nodes (Fig. 4), is very simple to say, that is node,,Web2- closer to transmitter than node,,Webl,,. Both nodes are placed on fix position and both have identical parameters and identical settings, because of that, we can simply estimate remote distance influence at interdependence with object response time and page response time. Results of the simulations are shown on Fig. 5-6 and 8-9. Fig. 7 shows us UMTS structure for VoIP application. Section 5 concludes the paper. Članek opisuje posamezne gradnike omrežja UMTS (Universal Mobile Telecommunication System), in njegovo simulacijo s programom Opnet Modeler. V fazi simuliranja omrežja se bomo omejili na dejavnike, ki vplivajo na kakovost posamezne storitve (aplikacije), predvsem pa na vpliv oddaljenosti in kvaliteto sprejema. Slednjo smo ovrednotili s pomočjo odzivnih časov pri spletni aplikaciji in telefoniji IP (ang. Internet Protocol).

Robotics is fast growing area, which achieves full bloom in last teen years. Now days, manipulators are indispensable part in industry. We use them for weld chassis, for steel and wood cultivation, for disperse coloring, steel cutting and so on. Since 1992, for each year, number of robots rapidly increases. Reason for that is their universality, but because of that property, people start initiates them into farms, agricultures, green houses, warehouses, into electronics production for composing electronic components...Today, robots using area expands wide around, specially to our homes. Basically view, represent robot as movement machine or automatic machine with more free programmable axels, in some cases in combination with sensors or computer vision. Our system consists with seven basic parts: the first one is operator and then follows programming device, microcontroller, robot hand, grasper, sensor and round movement ribbon. The main goal of this project is to incorporate all basic parts in to working process for composing elements of woody children house. Second section in this article represents components, which are extremely important when we initiate robotization into industry. Here belong criteria, like choosing real and successful first application, choosing right robot, production speed, time requirements for implement equipment, and complexity of automation. In third section we made case study of hold comparison between human and robot, which is very importantfor understanding, how servofloat function work. Fig. 1 shows round movement riboon, with basic parts on taking away place. Servofloat function isdescribed in session six. Fig. 3 represent barrier on trajectory between step 1 and step 2. With servofloat function can robot avoid this barrier and jump directly over shortest path to step 3. Chapter four give us some information about IR sensor, and basic work principle for light and dark places recognition. Table 1 shows possible combination, when we recognized parts of house, and Fig.2 shows basic principle of component recognition. Section five describes constructing algorithm procedure, where table 2 and their indicators illustrates course of construction phase. Chapters seven and eight are purposed for discussion about picking up elements from moving round ribbon and taking off the same elements on composing place. In this two sections we try to find answers on our problems, and solve them completely with suggest simple solutions. Fig. 4 under seven section illustrates left side element on round ribbon palette. Fig. 5 is placed in eight section, where illustrates decreasing tolerance between both big side elements. Under same section, Fig. 6 illustrates cultivated bottom side of the smallest side element. Section 9 concludes the paper. V članku predstavljamo princip prepoznavanja, pobiranja, odlaganja in sestavljanja elementov lesene otroške hiške. Na kratko želimo predstaviti vzroke problematike robotskega sestavljanja in uporabljene rešitve, ki so pripomogle k rešitvi problematike sestavljanja. Za lažjo predstavo smo izvedli primerjavo uporabljenih rešitev s tistimi, ki se v industriji uporabljajo kot profesionalne rešitve.