In the recent years, cloud services are dominating the internet world. Streaming video content is drastically increased. This trend created a way for the cloud gaming industry. Gaming Anywhere is one such an open source cloud gaming system designed specifically for gaming users to experience high-quality gaming while eliminating the burden of upgrading hardware or software whenever the gaming system becomes outdated. Gaming Anywhere client can stream the desired game from a remote server with high-quality resolution and fps. Gaming Anywhere launches almost all type of games as per the request of the client. In this paper, the performance of a Gaming Anywhere server is evaluated in a virtual windows environment. Performance is categorically divided into two types. One is server metrics and the other is power consumption. Server metrics deals with CPU utilization, GPU utilization and multi-player capability. Power consumption deals with the CPU power usage of a virtual machine. The main aim of this paper is to conduct measurement studies on Gaming Anywhere server in two virtual implementation kits, VMware and VirtualBox, using monitoring tools. The analysis of the outcome is evaluated against the Gaming Anywhere physical server.

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Performing social network analysis (SNA) requires a set of powerful techniques to analyze structural information contained in interactions between social entities. Many SNA technologies and methodologies have been developed and have successfully provided significant insights for small-scale interactions. However, these techniques are not suitable for analyzing large social networks, which are very popular and important in various fields and have special structural properties that cannot be obtained from small networks or their analyses. There are a number of issues that need to be further studied in the design of current SNA techniques. A number of key issues can be embodied in three fundamental and critical challenges: long processing time, large computational resource requirements, and network dynamism. In order to address these challenges, we discuss an anytime-anywhere methodology based on a parallel/distributed computational framework to effectively and efficiently analyze large and dynamic social networks. In our methodology, large social networks are decomposed into intra-related smaller parts. A coarse-level of network analysis is built based on comprehensively analyzing each part. The partial analysis results are incrementally refined over time. Also, during the analyses process, network dynamic changes are effectively and efficiently adapted based on the obtained results. In order to evaluate and validate our methodology, we implement our methodology for a set of SNA metrics which are significant for SNA applications and cover a wide range of difficulties. Through rigorous theoretical and experimental analyses, we demonstrate that our anytime-anywhere methodology is / Ph. D.

This research studies the three market-leading RPA-tools, Automation Anywhere, Blue Prism and UiPath, in order to fill the lack of literature regarding methods for evaluating and comparing RPA-tools. Design science research was performed by designing and creating artefacts in the form of process implementations and an evaluative model. A typical process representing a common area of use was implemented using each of the three RPA-tools, in order to create an evaluative model. Official documentation, along with the three implementations, were studied. Evaluative questions specific to RPA-tool evaluation were created based on a quality model for product quality found in the ISO/IEC 25010 standard. Characteristics dependant on organisational context were not included in the evaluation, in order to create an evaluative model which is not dependant on any specific business environment. The results of the research provide knowledge of (1) how RPA-tools can be implemented and (2) the differences that exist between the three market-leading RPA tools. The research also contributes in the form of a method for investigating and evaluating the RPA-tools. When creating the evaluative model, some of the criteria found in the ISO/IEC 25010 quality model were concluded to be of low relevance and, therefore, not included in the model. By analysing and evaluating the created evaluative model, using a theoretical concept of digital resources and their evaluation, the validity of the evaluative model was reinforced. From an evaluative perspective, this research emphasises the need to appropriate and change existing evaluative methods in order to successfully evaluate the most relevant characteristics of RPA-tools. / Denna forskning studerar de tre marknadsledande RPA-verktygen, Automation Anywhere, Blue Prism och UiPath, för att fylla bristen på litteratur om metoder för utvärdering och jämförelse av RPA-verktyg. Design science research genomfördes genom att utforma och skapa artefakter i form av processimplementeringar och en utvärderingsmodell. En typisk process som representerar ett vanligt användningsområde implementerades med användning av vart och ett av de tre RPA-verktygen för att skapa en utvärderingsmodell. Officiell dokumentation, tillsammans med de tre implementeringarna, studerades. Utvärder-ingsfrågor specifika för RPA-verktygsutvärdering skapades baserat på en kvalitetsmodell för produktkvalitet som finns i ISO/IEC 25010-standarden. Egenskaper som är beroende av organisatoriskt sammanhang ingick inte i utvärderingen för att skapa en utvärderingsmodell som inte är beroende av någon specifik affärsmiljö. Resultaten av forskningen ger kunskap om (1) hur RPA-verktyg kan implementeras och (2) skillnaderna som finns mellan de tre marknadsledande RPA-verktygen. Forskningen bidrar också i form av en metod för att undersöka och utvärdera RPA-verktygen. Vid skapandet av utvärderingsmodellen drogs slutsatsen att några av kriterierna i kvalitetsmodellen i ISO/IEC 25010 var av låg relevans och de är därför inte inkluderade i den resulterande modellen. Genom att analysera och utvärdera den skapade utvärderingsmodellen, med hjälp av ett teoretiskt koncept av digitala resurser och deras utvärdering, förstärktes utvärderingsmodellens validitet. Ur ett utvärderingsperspektiv betonar denna forskning behovet av att anpassa och ändra befintliga utvärderingsmetoder för att framgångsrikt utvärdera de mest relevanta egenskaperna hos RPA-verktyg.