Use of Cloud Gaming in Education

The use of digital games in education has been the subject of research for many years and their usefulness has been confirmed by many studies and research projects. Standardized tests, such as PISA test, show that respondents achieved better reading, math and physics results if they used the computer more for gaming-related activities. It has been proven that the application of video games in education increases student motivation, improves several types of key skills—social and intellectual skills, reflexes and concentration. Nevertheless, there are several challenges associated with the application of video games in schools and they can be categorized as technical (network and end device limitations), competency (teachers’ knowledge in the area), qualitative (lack of educational games of high quality), and financial (high cost of purchasing games and equipment). The novel architecture for delivery of gaming content commonly referred to as “cloud gaming” has the potential to solve most of the present challenges of using games in education. A well-designed cloud gaming platform would enable seamless and simple usage for both students and teachers. While solving most of the present problems, cloud gaming introduces a set of new research challenges which will be discussed in this section

Towards a new ITU-T recommendation for subjective methods evaluating gaming QoE

This paper reports on activities in Study Group 12 of the International Telecommunication Union (ITU-T SG12) to define a new Recommendation on subjective evaluation methods for gaming Quality of Experience (QoE). It first resumes the structure and content of the current draft which has been proposed to ITU-T SG12 in September 2014 and then critically discusses potential gaming content and evaluation methods for inclusion into the upcoming Recommendation. The aim is to start a discussion amongst experts on potential evaluation methods and their limitations, before finalizing a Recommendation. Such a recommendation might in the end be applied by non -expert users, hence wrong decisions in the evaluation design could negatively affect gaming QoE throughout the evaluation

Scalable software architecture for distributed MMORPG traffic generation based on integration of UrBBaN-Gen and IMUNES

We present a scalable software architecture for distributed traffic generation capable of producing Massively Multiplayer Online Role-Playing Game (MMORPG) packet flows in a statistically accurate manner for thousands of concurrent players. The main challenge, to achieve truly massive scale traffic generation, has been achieved by introducing kernel based virtualization, pioneered by the network simulator/emulator IMUNES, into the User Behaviour Based Network Traffic Generation (UrBBan-Gen, introduced in our earlier work). The UrBBan-Gen software architecture consists of four modules: Service repository, Control function and user interface, Behaviour process, and Traffic generation process. IMUNES has been integratedinto the virtualization part of the Traffic generation process,which has resulted in two improvements: 1) increasing thenumber of generated packet flows while accurately replicating the required statistical properties, and, 2) introducing the ability to run various network scenarios in simulated, as well as real networks, under realistic traffic loads. With respect to the traffic generation capabilities of the previous version of UrBBan-Gen, which was based on Linux containers, the IMUNES based solution demonstrates higher scalability, lower packet loss rates, and lower CPU load for both the UDP traffic at high packet rate and “thin” TCP traffic flows typical for MMORPGs

Modeliranje mrežnog prometa višekorisničkih igara s preuzimanjem uloga temeljeno na korisnikovom ponašanju

While network traffic characteristics of Massively Multiplayer Online Role-Playing Games (MMORPG) are known to be very variable and somehow linked to game dynamics and user behaviour, the actual relationships have, thus far, not been described in a comprehensive and unified way, which could sucessfully be applied for synthetic traffic generation. This thesis aims to fill this gap by proposing a novel source based MMORPG traffic model, which explains and captures observed variations of traffic characteristics. The proposed model takes user behaviour at the application level as a starting point. As networked virtual worlds of MMORPGs are very complex, there is a wide variety of in-game situations based on “what users do” in the virtual world, which reflect onto network traffic in different ways. The model focuses on capturing, recognizing, understanding, and describing the relationships between user actions and network traffic. A classification proposed in this thesis distinguishes between the following user action categories: Trading, Questing, Player versus player combat, Dungeons, and Raiding. For each action category, a traffic model capturing the statistical characteristics of network traffic has been developed and validated through network traffic measurements. Client and server application protocol data unit size and interrarival time have been modeled by a combination of several distributions, including Weibull, Normal, Lognormal, Largest Extreme Value, and Deterministic. Next, the player behaviour over a sin-gle gaming session has been studied and modelled based on the defined action categories by using a first order Markov chain. Finally, the aggregate behaviour of all active users on a single MMORPG server has been described. The arrival of new players and departure of leaving players are modeled as a Homogeneous Poisson Process (HPP). Based on the proposed model, a functional architecture of a MMORPG traffic generator based on player behaviour, called UrBBaN-Gen, has been developed and implemented by using Java, Python and bash scripts, together with the open source software traffic generator – Distributed Internet Traffic Generator (D-ITG). Synthetic traffic generated by UrBBaN-Gen has been compared with independent empirical traces, and it has been demonstrated that the characteristics of the generated traffic closely follow the real traffic. Also, the model has been compared with the models found in literature, and its advantages over the existing models have been shown. The contribution of this thesis may be summarized as follows: Classification of user actions in the virtual world of MMORPGs, and characterization of associated network traffic ; User behaviour model based on categories of user actions, motivational parameters, and identified behavioural patterns on application level ; and Architecture and implementation of traffic generator based on the model and verification of the model through comparison of synthetic and real traffic.Karakteristike mrežnog prometa koji generiraju višekorisničke igre s preuzimanjem uloga su vrlo promjenjive. Varijacije u mrežnom opterećenju mogu dostizati i razliku od deset puta između najniže i najviše vrijednosti. Treba uzeti u obzir da je riječ o prosječnim vrijednostima u vremenskim periodima na razini minuta, pa čak i sati. U ovoj disertaciji predložen je izvorišni model mrežnog prometa. Izvorišni modeli mrežnog prometa temelje se na ponašanju aplikacija koje se nalaze na krajnjim točkama mreže. Predloženi model objašnjava i obuhvaća uočene varijacije karakteristika mrežnog prometa. Model se temelji na ponašanju korisnika unutar višekorisničkih igara s preuzimanjem uloga. Kao studijski slučaj koristi se umrežena igra World of Warcraft proizvođača Activision Blizzard. Kako su virtualni svjetovi ovih igara vrlo složeni, a broj interakcija i situacija u kojem se korisnik može naći velik, za potrebe modeliranja predložena je klasifikacija korisničkih akcija. Predložene kategorije korisničkih akcija su: trgovanje, traganje ili izvršavanje zadataka, borba između igrača, napadanje tamnica i masovno napadanje tamnica. Različitost identificiranih kategorija ponašanja potvrđena je kroz mjerenje i usporedbu karakteristika mrežnog prometa pojedinačne kategorije. Za svaku kategoriju kreiran je matematički model mrežnog prometa koji se sastoji od kompleksnih statističkih distribucija koje opisuju veličinu jedinica podataka koji se šalju na razini aplikacije (ne na razini, primjerice, datagrama protokola IP), te međudolazna vremena između dva uzastopna slanja jedinica podataka. Na temelju identificiranih kategorija provedena su mjerenja ponašanja korisnika pomoću kojih je kreiran model ponašanja korisnika. Kreirani model opisuje ponašanje pojedinačnog korisnika, ali i zbirno ponašanje svih korisnika na razini usluge. Također, proučen je odnos između psihološke motivacije korisnika i njihovog ponašanja na razini aplikacije. Razvijeni modeli ponašanja korisnika i njihov utjecaj na mrežne karakteristike prometa objedinjeni su kroz funkcijsku arhitekturu programskog generatora mrežnog prometa utemeljenog na ponašanju korisnika (engl. User Behaviour Based Network Traffic Generator - UrBBaN-Gen.). UrBBaN-Gen čine tri programska modula: 1) simulator korisničkog ponašanja, 2) sustav za kontrolu distribuiranog generiranja prometa te 3) generator mrežnog prometa. Simulator korisničkog ponašanja razvijen je primjenom programskog jezika Java, a sustav za kontrolu distribuiranog generiranja prometa primjenom Jave te Python i Bash skripti. Generator mrežnog prometa temelji se na softveru otvorenog koda Distribuirani internetski mrežni generator (engl. Distributed Internet Traffic Generator -- D-ITG), koji je modificiran kako bi se u njega ugradili modeli prometa predloženih kategorija korisničkih akcija. Razvijeni model mrežnog prometa je uspoređen s modelima za istu uslugu poznatima u literaturi te su pokazane njegove prednosti. Također, model je verificiran kroz usporedbu sintetičkog, računalno generiranog prometa sa stvarnim prometom, te je pokazano da karakteristike generiranog prometa zadovoljavajuće sliče karakteristikama stvarnog prometa. Znanstveni doprinos disertacije je sljedeći: 1. Klasifikacija tipova korisničkih akcija unutar virtualnih okruženja igara s preuzimanjem uloga i karakterizacija pripadajućeg mrežnog prometa, 2. Model ponašanja korisnika, temeljen na kategorijama korisničkih akcija, motivacijskim parametrima te identificiranim uzorcima ponašanja na razini aplikacije, i 3. Arhitektura i programska izvedba generatora mrežnog prometa zasnovanog na modelu i verifikacija modela kroz usporedbu sintetiziranog i stvarnog mrežnog prometa

Modeliranje mrežnog prometa višekorisničkih igara s preuzimanjem uloga temeljeno na korisnikovom ponašanju

While network traffic characteristics of Massively Multiplayer Online Role-Playing Games (MMORPG) are known to be very variable and somehow linked to game dynamics and user behaviour, the actual relationships have, thus far, not been described in a comprehensive and unified way, which could sucessfully be applied for synthetic traffic generation. This thesis aims to fill this gap by proposing a novel source based MMORPG traffic model, which explains and captures observed variations of traffic characteristics. The proposed model takes user behaviour at the application level as a starting point. As networked virtual worlds of MMORPGs are very complex, there is a wide variety of in-game situations based on “what users do” in the virtual world, which reflect onto network traffic in different ways. The model focuses on capturing, recognizing, understanding, and describing the relationships between user actions and network traffic. A classification proposed in this thesis distinguishes between the following user action categories: Trading, Questing, Player versus player combat, Dungeons, and Raiding. For each action category, a traffic model capturing the statistical characteristics of network traffic has been developed and validated through network traffic measurements. Client and server application protocol data unit size and interrarival time have been modeled by a combination of several distributions, including Weibull, Normal, Lognormal, Largest Extreme Value, and Deterministic. Next, the player behaviour over a sin-gle gaming session has been studied and modelled based on the defined action categories by using a first order Markov chain. Finally, the aggregate behaviour of all active users on a single MMORPG server has been described. The arrival of new players and departure of leaving players are modeled as a Homogeneous Poisson Process (HPP). Based on the proposed model, a functional architecture of a MMORPG traffic generator based on player behaviour, called UrBBaN-Gen, has been developed and implemented by using Java, Python and bash scripts, together with the open source software traffic generator – Distributed Internet Traffic Generator (D-ITG). Synthetic traffic generated by UrBBaN-Gen has been compared with independent empirical traces, and it has been demonstrated that the characteristics of the generated traffic closely follow the real traffic. Also, the model has been compared with the models found in literature, and its advantages over the existing models have been shown. The contribution of this thesis may be summarized as follows: Classification of user actions in the virtual world of MMORPGs, and characterization of associated network traffic ; User behaviour model based on categories of user actions, motivational parameters, and identified behavioural patterns on application level ; and Architecture and implementation of traffic generator based on the model and verification of the model through comparison of synthetic and real traffic.Karakteristike mrežnog prometa koji generiraju višekorisničke igre s preuzimanjem uloga su vrlo promjenjive. Varijacije u mrežnom opterećenju mogu dostizati i razliku od deset puta između najniže i najviše vrijednosti. Treba uzeti u obzir da je riječ o prosječnim vrijednostima u vremenskim periodima na razini minuta, pa čak i sati. U ovoj disertaciji predložen je izvorišni model mrežnog prometa. Izvorišni modeli mrežnog prometa temelje se na ponašanju aplikacija koje se nalaze na krajnjim točkama mreže. Predloženi model objašnjava i obuhvaća uočene varijacije karakteristika mrežnog prometa. Model se temelji na ponašanju korisnika unutar višekorisničkih igara s preuzimanjem uloga. Kao studijski slučaj koristi se umrežena igra World of Warcraft proizvođača Activision Blizzard. Kako su virtualni svjetovi ovih igara vrlo složeni, a broj interakcija i situacija u kojem se korisnik može naći velik, za potrebe modeliranja predložena je klasifikacija korisničkih akcija. Predložene kategorije korisničkih akcija su: trgovanje, traganje ili izvršavanje zadataka, borba između igrača, napadanje tamnica i masovno napadanje tamnica. Različitost identificiranih kategorija ponašanja potvrđena je kroz mjerenje i usporedbu karakteristika mrežnog prometa pojedinačne kategorije. Za svaku kategoriju kreiran je matematički model mrežnog prometa koji se sastoji od kompleksnih statističkih distribucija koje opisuju veličinu jedinica podataka koji se šalju na razini aplikacije (ne na razini, primjerice, datagrama protokola IP), te međudolazna vremena između dva uzastopna slanja jedinica podataka. Na temelju identificiranih kategorija provedena su mjerenja ponašanja korisnika pomoću kojih je kreiran model ponašanja korisnika. Kreirani model opisuje ponašanje pojedinačnog korisnika, ali i zbirno ponašanje svih korisnika na razini usluge. Također, proučen je odnos između psihološke motivacije korisnika i njihovog ponašanja na razini aplikacije. Razvijeni modeli ponašanja korisnika i njihov utjecaj na mrežne karakteristike prometa objedinjeni su kroz funkcijsku arhitekturu programskog generatora mrežnog prometa utemeljenog na ponašanju korisnika (engl. User Behaviour Based Network Traffic Generator - UrBBaN-Gen.). UrBBaN-Gen čine tri programska modula: 1) simulator korisničkog ponašanja, 2) sustav za kontrolu distribuiranog generiranja prometa te 3) generator mrežnog prometa. Simulator korisničkog ponašanja razvijen je primjenom programskog jezika Java, a sustav za kontrolu distribuiranog generiranja prometa primjenom Jave te Python i Bash skripti. Generator mrežnog prometa temelji se na softveru otvorenog koda Distribuirani internetski mrežni generator (engl. Distributed Internet Traffic Generator -- D-ITG), koji je modificiran kako bi se u njega ugradili modeli prometa predloženih kategorija korisničkih akcija. Razvijeni model mrežnog prometa je uspoređen s modelima za istu uslugu poznatima u literaturi te su pokazane njegove prednosti. Također, model je verificiran kroz usporedbu sintetičkog, računalno generiranog prometa sa stvarnim prometom, te je pokazano da karakteristike generiranog prometa zadovoljavajuće sliče karakteristikama stvarnog prometa. Znanstveni doprinos disertacije je sljedeći: 1. Klasifikacija tipova korisničkih akcija unutar virtualnih okruženja igara s preuzimanjem uloga i karakterizacija pripadajućeg mrežnog prometa, 2. Model ponašanja korisnika, temeljen na kategorijama korisničkih akcija, motivacijskim parametrima te identificiranim uzorcima ponašanja na razini aplikacije, i 3. Arhitektura i programska izvedba generatora mrežnog prometa zasnovanog na modelu i verifikacija modela kroz usporedbu sintetiziranog i stvarnog mrežnog prometa

Modeliranje mrežnog prometa višekorisničkih igara s preuzimanjem uloga temeljeno na korisnikovom ponašanju

While network traffic characteristics of Massively Multiplayer Online Role-Playing Games (MMORPG) are known to be very variable and somehow linked to game dynamics and user behaviour, the actual relationships have, thus far, not been described in a comprehensive and unified way, which could sucessfully be applied for synthetic traffic generation. This thesis aims to fill this gap by proposing a novel source based MMORPG traffic model, which explains and captures observed variations of traffic characteristics. The proposed model takes user behaviour at the application level as a starting point. As networked virtual worlds of MMORPGs are very complex, there is a wide variety of in-game situations based on “what users do” in the virtual world, which reflect onto network traffic in different ways. The model focuses on capturing, recognizing, understanding, and describing the relationships between user actions and network traffic. A classification proposed in this thesis distinguishes between the following user action categories: Trading, Questing, Player versus player combat, Dungeons, and Raiding. For each action category, a traffic model capturing the statistical characteristics of network traffic has been developed and validated through network traffic measurements. Client and server application protocol data unit size and interrarival time have been modeled by a combination of several distributions, including Weibull, Normal, Lognormal, Largest Extreme Value, and Deterministic. Next, the player behaviour over a sin-gle gaming session has been studied and modelled based on the defined action categories by using a first order Markov chain. Finally, the aggregate behaviour of all active users on a single MMORPG server has been described. The arrival of new players and departure of leaving players are modeled as a Homogeneous Poisson Process (HPP). Based on the proposed model, a functional architecture of a MMORPG traffic generator based on player behaviour, called UrBBaN-Gen, has been developed and implemented by using Java, Python and bash scripts, together with the open source software traffic generator – Distributed Internet Traffic Generator (D-ITG). Synthetic traffic generated by UrBBaN-Gen has been compared with independent empirical traces, and it has been demonstrated that the characteristics of the generated traffic closely follow the real traffic. Also, the model has been compared with the models found in literature, and its advantages over the existing models have been shown. The contribution of this thesis may be summarized as follows: Classification of user actions in the virtual world of MMORPGs, and characterization of associated network traffic ; User behaviour model based on categories of user actions, motivational parameters, and identified behavioural patterns on application level ; and Architecture and implementation of traffic generator based on the model and verification of the model through comparison of synthetic and real traffic.Karakteristike mrežnog prometa koji generiraju višekorisničke igre s preuzimanjem uloga su vrlo promjenjive. Varijacije u mrežnom opterećenju mogu dostizati i razliku od deset puta između najniže i najviše vrijednosti. Treba uzeti u obzir da je riječ o prosječnim vrijednostima u vremenskim periodima na razini minuta, pa čak i sati. U ovoj disertaciji predložen je izvorišni model mrežnog prometa. Izvorišni modeli mrežnog prometa temelje se na ponašanju aplikacija koje se nalaze na krajnjim točkama mreže. Predloženi model objašnjava i obuhvaća uočene varijacije karakteristika mrežnog prometa. Model se temelji na ponašanju korisnika unutar višekorisničkih igara s preuzimanjem uloga. Kao studijski slučaj koristi se umrežena igra World of Warcraft proizvođača Activision Blizzard. Kako su virtualni svjetovi ovih igara vrlo složeni, a broj interakcija i situacija u kojem se korisnik može naći velik, za potrebe modeliranja predložena je klasifikacija korisničkih akcija. Predložene kategorije korisničkih akcija su: trgovanje, traganje ili izvršavanje zadataka, borba između igrača, napadanje tamnica i masovno napadanje tamnica. Različitost identificiranih kategorija ponašanja potvrđena je kroz mjerenje i usporedbu karakteristika mrežnog prometa pojedinačne kategorije. Za svaku kategoriju kreiran je matematički model mrežnog prometa koji se sastoji od kompleksnih statističkih distribucija koje opisuju veličinu jedinica podataka koji se šalju na razini aplikacije (ne na razini, primjerice, datagrama protokola IP), te međudolazna vremena između dva uzastopna slanja jedinica podataka. Na temelju identificiranih kategorija provedena su mjerenja ponašanja korisnika pomoću kojih je kreiran model ponašanja korisnika. Kreirani model opisuje ponašanje pojedinačnog korisnika, ali i zbirno ponašanje svih korisnika na razini usluge. Također, proučen je odnos između psihološke motivacije korisnika i njihovog ponašanja na razini aplikacije. Razvijeni modeli ponašanja korisnika i njihov utjecaj na mrežne karakteristike prometa objedinjeni su kroz funkcijsku arhitekturu programskog generatora mrežnog prometa utemeljenog na ponašanju korisnika (engl. User Behaviour Based Network Traffic Generator - UrBBaN-Gen.). UrBBaN-Gen čine tri programska modula: 1) simulator korisničkog ponašanja, 2) sustav za kontrolu distribuiranog generiranja prometa te 3) generator mrežnog prometa. Simulator korisničkog ponašanja razvijen je primjenom programskog jezika Java, a sustav za kontrolu distribuiranog generiranja prometa primjenom Jave te Python i Bash skripti. Generator mrežnog prometa temelji se na softveru otvorenog koda Distribuirani internetski mrežni generator (engl. Distributed Internet Traffic Generator -- D-ITG), koji je modificiran kako bi se u njega ugradili modeli prometa predloženih kategorija korisničkih akcija. Razvijeni model mrežnog prometa je uspoređen s modelima za istu uslugu poznatima u literaturi te su pokazane njegove prednosti. Također, model je verificiran kroz usporedbu sintetičkog, računalno generiranog prometa sa stvarnim prometom, te je pokazano da karakteristike generiranog prometa zadovoljavajuće sliče karakteristikama stvarnog prometa. Znanstveni doprinos disertacije je sljedeći: 1. Klasifikacija tipova korisničkih akcija unutar virtualnih okruženja igara s preuzimanjem uloga i karakterizacija pripadajućeg mrežnog prometa, 2. Model ponašanja korisnika, temeljen na kategorijama korisničkih akcija, motivacijskim parametrima te identificiranim uzorcima ponašanja na razini aplikacije, i 3. Arhitektura i programska izvedba generatora mrežnog prometa zasnovanog na modelu i verifikacija modela kroz usporedbu sintetiziranog i stvarnog mrežnog prometa

Enabling Video Games in Education Through Cloud Gaming

The use of digital games in education has been the subject of research for many years and their usefulness has been confirmed by many studies and research projects. Standardized tests, such as PISA test, show that respondents achieved better reading, math and physics results if they used the computer more for gaming-related activities. It has been proven that the application of video games in education increases student motivation, improves several types of key skills – social and intellectual skills, reflexes and concentration. Nevertheless, there are several challenges associated with the application of video games in schools, and they can be categorized as technical (network and end device limitations), competency (teachers’ knowledge in the area), qualitative (lack of educational games of high quality), and financial (high cost of purchasing games and equipment). The novel architecture for delivery of gaming content commonly referred to as “cloud gaming” has the potential to solve most of the present challenges of using games in education. In cloud gaming, the game is completely stored and played on a server located on a cloud with a high-definition video sent to the client, and user commands sent to the server. A well-designed cloud gaming platform would enable seamless and simple usage for both students and teachers. While solving most of the present problems, cloud gaming introduces a set of new research challenges which will be discussed in this paper. These challenges include Quality of Experience based optimization for video coding based on network constraints, simplification of procedures for usage of the platform for students and teachers, and methodology for content adaptation and creation. This paper presents a roadmap of research which needs to be conducted in order to develop a cloud gaming system which can be used in education

Enabling Video Games in Education Through Cloud Gaming

The use of digital games in education has been the subject of research for many years and their usefulness has been confirmed by many studies and research projects. Standardized tests, such as PISA test, show that respondents achieved better reading, math and physics results if they used the computer more for gaming-related activities. It has been proven that the application of video games in education increases student motivation, improves several types of key skills – social and intellectual skills, reflexes and concentration. Nevertheless, there are several challenges associated with the application of video games in schools, and they can be categorized as technical (network and end device limitations), competency (teachers’ knowledge in the area), qualitative (lack of educational games of high quality), and financial (high cost of purchasing games and equipment). The novel architecture for delivery of gaming content commonly referred to as “cloud gaming” has the potential to solve most of the present challenges of using games in education. In cloud gaming, the game is completely stored and played on a server located on a cloud with a high-definition video sent to the client, and user commands sent to the server. A well-designed cloud gaming platform would enable seamless and simple usage for both students and teachers. While solving most of the present problems, cloud gaming introduces a set of new research challenges which will be discussed in this paper. These challenges include Quality of Experience based optimization for video coding based on network constraints, simplification of procedures for usage of the platform for students and teachers, and methodology for content adaptation and creation. This paper presents a roadmap of research which needs to be conducted in order to develop a cloud gaming system which can be used in education

Theoretical and Empirical Analysis of a Fast Algorithm for Extracting Polygons from Signed Distance Bounds

Recently, there has been renewed interest in signed distance bound representations due to their unique properties for 3D shape modelling. This is especially the case for deep learning-based bounds. However, it is beneficial to work with polygons in most computer graphics applications. Thus, in this paper, we introduce and investigate an asymptotically fast method for transforming signed distance bounds into polygon meshes. This is achieved by combining the principles of sphere tracing (or ray marching) with traditional polygonization techniques, such as marching cubes. We provide theoretical and experimental evidence that this approach is of the O(N2logN) computational complexity for a polygonization grid with N3 cells. The algorithm is tested on both a set of primitive shapes and signed distance bounds generated from point clouds by machine learning (and represented as neural networks). Given its speed, implementation simplicity, and portability, we argue that it could prove useful during the modelling stage as well as in shape compression for storage