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Analiza bremena in zmogljivosti vzorčnega e-zdravstvenega sistema
ID Škufca, Ladislav (Author), ID Mraz, Miha (Mentor) More about this mentor... This link opens in a new window

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Abstract
Ob izvajanju zmogljivostnega testiranja nekega sistema nas mnogokrat zanima, kako bi se sistem odzval na večjo obremenitev. Da bi pri testiranju pridobili čim bolj realne rezultate, uporabimo sintetično in ne povsem umetno breme, saj sintetično breme odraža določene lastnosti realnega bremena. Pričujoče magistrsko delo razvije metodologijo za analizo bremena vzorčnega e-zdravstvenega sistema, katere cilj je pridobiti čimbolj natančne podatke o realnem bremenu, da bi na osnovi slednjega lahko prišli do izhodišč formacije sintetičnega bremena, ki ga običajno uporabimo za potrebe izvajanja stresnih in bremenskih testov vzorčnega sistema. V magistrski nalogi sprva razložimo pojem e-zdravstva in predstavimo vzorčni sistem, na katerem smo pridobili vzorčno breme. Nadaljujemo z opisom teorije strežbe, definiranjem osnovnih metrik bremena in s predstavitvijo izračuna medprihodnih časov zahtev po Poissonovi ter Paretovi verjetnostni porazdelitvi. Ključna koraka analize bremena predlagamo v dveh korakih. Prvi korak zajema pridobivanje oziroma obdelovanje podatkov o vzorčnem bremenu. Drugi korak zajema analiziranje obdelanih podatkov, kar predstavlja osnovo za definiranje sintetičnega bremena. V okviru prvega koraka je naš fokus na zajemu in obdelavi zahtev HTTP. Ključno vlogo v magistrskem delu igrajo uporabniške akcije, ki jih sestavlja množica zaporednih zahtev HTTP. Za namen obdelave podatkov o akcijah razvijemo lastno orodje v programskem jeziku Java. Rezultat procesa zajema in obdelave podatkov je frekvenčna porazdelitev medprihodnih časov akcij, ki jih je uporabnik izvajal v vzorčnem sistemu. Porazdelitev grafično prikažemo na histogramu. V okviru drugega koraka se osredotočimo na metriko porazdelitev vstopanja zahtev v strežni sistem. Podrobneje analiziramo dinamiko medprihodnih časov zahtev in akcij. Porazdelitev medprihodnih časov akcij primerjamo s porazdelitvijo medprihodnih časov po Poissonovi in Paretovi verjetnostni porazdelitvi. Odločitev o porazdelitvi, ki v največji meri sovpada z našo porazdelitvijo medprihodnih časov akcij, sprejmemo na podlagi rezultatov uporabe Jensen-Shannonove divergence. Rezultat tega koraka je definiranje enačbe za izračun medprihodnih časov, ki bi služila kot izhodišče pri formaciji sintetičnega bremena.

Language:Slovenian
Keywords:računalniška zmogljivost, računalniško breme, e-zdravstvo
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2020
PID:20.500.12556/RUL-120786 This link opens in a new window
COBISS.SI-ID:32878083 This link opens in a new window
Publication date in RUL:25.09.2020
Views:780
Downloads:138
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Secondary language

Language:English
Title:Analysis of load and performance of a sample e-health system
Abstract:
While performance testing a system, we are curious about how would the system perform with a bigger load. To get as real results as possible, we use a synthetic load instead of a fully artificial load. Synthetic load reflects some of the properties of the real load. This master thesis develops a methodology for the analysis of the load of a sample e-health system. The methodology aims to get as much detailed data of real load so the data can be used as a starting point for forming synthetic load, which we usually use in case of stress and load testing of sample systems. In this master thesis, we first explain the concept of e-health and introduce the sample system, which was used to obtain the sample load. We continue with queueing theory, the definition of basic load metrics, and with a presentation of calculating interarrival times for requests with Poisson and Pareto probability distribution. The analysis is suggested in two main steps. The first step consists of obtaining and processing of the data in the sample load. The second step consists of the analysis of the processed data which represents the groundwork for defining synthetic load. In the first step, we focus on capturing and processing of HTTP requests. User actions play a key role in this master thesis. They consist of consecutive HTTP requests. For the purpose of processing action data, we develop our own tool, written in the Java programming language. The result of capturing and processing the data is a frequency distribution of interarrival times for actions that the user performed in the sample system. The distribution is graphically shown on a histogram. In the second step, we focus on metrics of interarrival times of requests in the serving system. In detail, we analyze the dynamics of interarrival times of requests and actions. We compare the distribution of interarrival times of actions with Poisson and Pareto probability distributions. The decision for the distribution which largely coincides with our distribution of interarrival times of actions is based on the results of the Jensen-Shannon divergence. The final result of this step is a definition of the equation to calculate interarrival times, which can be used as the groundwork for the definition of a synthetic load.

Keywords:computer performance, computer load, e-health

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