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Multiplayer games can increase player enjoyment through social interactions, cooperation and competition. The popularity of such games is shown by current market trends. Especially networked multiplayer games frequently achieve great success, but confront game developers with additional networking challenges in the already complex field of game production. The primary challenge is game state synchronization across all players. Based on the current research, there are three main methods for this task – deterministic lockstep, snapshot interpolation and state-sync – with their own advantages and disadvantages.
This work quantitatively evaluated and discussed the vertical (entity count) and horizontal (player count) limitations of deterministic lockstep and compared the method to snapshot interpolation. Results showed, that deterministic lockstep has no indicated vertical scaling limitation with a player count of up to 10 supporting 16,000 or more entities. A horizontal scaling limitation could not be found either and lockstep was confirmed to work with 40 or more players while handling 1024 entities. However, both scaling dimensions correlate negatively, which was indicated by the maximum scaling configurations 30 players and 4096 entities or 20 players and 8192 entities.
An unoptimized snapshot interpolation implementation achieved a vertical scaling limitation of 4096 entities with 10 players and a horizontal scaling limit of 40 or more players with 1024 entities and therefore was found to have a lower entity limit compared to deterministic lockstep.
Furthermore, results are compared to related work. Other contributions of this thesis include an overview of game networks and the three game state synchronization techniques. An architecture model for deterministic lockstep including a hybrid approach combining it with snapshot interpolation for re-synchronization and hot-joins. And finally, a network packet deconstruction of the implemented networking framework Unity Transport Package (UTP).
Multiplayer games can increase player enjoyment through social interactions, cooperation, and competition. Their market popularity shows the success of especially networked multiplayer games, which pose new networking challenges to game developers. The main challenge is synchronizing game state across players. Research identifies deterministic lockstep, snapshot interpolation, and state-sync as primary methods for this task, each with distinct advantages and disadvantages.
This work, and the master thesis this paper is based on, quantitatively evaluated deterministic lockstep, demonstrating its vertical (entity count) and horizontal (player count) scaling limitations and compares the method to snapshot interpolation. Lockstep supports minimum 16,000 entities for up to 10 players and a horizontal scaling of 40 or more players with 1024 entities. However, a negative correlation between entity and player count limits was observed, which was indicated by the maximum scaling configurations 30 players with 4096 entities or 20 players with 8192 entities. Snapshot interpolation faced a vertical limit with 4096 entities and 10 players and horizontally with 40 or more players and 1024 entities.
The paper further contributes by comparing results to related work, summarizing synchronization methods, proposing a hybrid architecture model of deterministic lockstep with snapshot interpolation for re-synchronization and hot-joins, and deconstructing Unity Transport Package’s (UTP) network packets.
Today’s digital cameras use a mosaic of red, green, and blue color filters to capture images in three color channels on a single sensor plane. This thesis investigates the use of convolutional neural networks (CNNs) for demosaicing – the process of reconstructing full-color images from raw mosaic sensor data. While there are existing CNNs for demosaicing raw images from the well-established regular Bayer color filter array (CFA), this thesis focuses on how they perform on alternative non-regular sampling patterns that produce less aliasing artifacts, namely the stochastic Gaussian- and the RandomQuarter sampling pattern (Backes and Fröhlich, 2020).
A basic UNet (Ronneberger et al., 2015) and the spatially adaptive SANet (T. Zhang et al., 2022) are implemented in a supervised training pipeline based on the PixelShift200 image dataset (Qian et al., 2021) to investigate their suitability for the irregular demosaicing task. The experiments indicate that the basic UNet encounters difficulties in restoring the missing color values, whereas the spatially adaptive convolutional layers help in processing the irregularly sampled raw images.
In addition, this thesis enhances SANet effectiveness by employing an alternative residual branch based on a CFA-normalized Gaussian filter, as well as a tileable modification to the Gaussian CFA pattern. The modified SANet is shown to outperform the conventional dFSR algorithm (Backes & Fröhlich, 2020) in terms of peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM).
Password-based authentication is widely used online, despite its numerous shortcomings, enabling attackers to take over users’ accounts. Phishing-resistant Fast IDentity Online (FIDO) credentials have therefore been proposed to improve account security and authentication user experience. With the recent introduction of FIDO-based passkeys, industry-leading corporations aim to drive widespread adoption of passwordless authentication to eliminate some of the most common account takeover attacks their users are exposed to. This thesis presents the first iteration of a distributed web crawler measuring the adoption of FIDO-based authentication methods on the web to observe ongoing developments and assess the viability of the promised passwordless future. The feasibility of automatically detecting authentication methods is investigated by analyzing crawled web content. Because today’s web is increasingly client-side rendered, capturing relevant data with traditional scraping methods is challenging. Thus, the traditional approach is compared to the browser-based crawling of dynamic content to optimize the detection rate. The results show that authentication method detection is possible, although there are some limitations regarding accuracy and coverage. Moreover, browser-based crawling is found to significantly increase detection rate.
Virtual-reality (VR) is an immersive technology with a growing market and many applications for gesture recognition. This thesis presents a VR gesture recognition method using signal processing techniques. The core concept is based on the comparison of motion features in the form of signals between a runtime recording of users and a possible gesture set. This comparison yields a similarity score through which the most similar gesture can be recognized by a continuous recognition system. Some selected comparison methods are presented, evaluated and discussed. An example implementation is demonstrated. However, due to an introduced layer model parts of the method and its implementation are interchangeable.
Similar or even better performance is achieved compared to other related work. The comparison method Dynamic Time Warping (DTW) reaches an average positive recognitions rate of 98.18% with acceptable real-time application performance. Additionally, the method comes with some benefits: position and direction of users is irrelevant, body proportions have no significant negative impact on recognition rates, faster and slower gesture executions are possible, no user inputs are needed to communicate gesture start and end (continuous recognition), also continuous gestures can be recognized, and the recognition is fast enough to trigger gesture specific events already during the execution.
The legitimacy of users is of great importance for the security of information systems. The authentication process is a trade-off between system security and user experience. E.g., forced password complexity or multi-factor authentication can increase protection, but the application becomes more cumbersome for the users. Therefore, it makes sense to investigate whether the identity of a user can be verified reliably enough, without his active participation, to replace or supplement existing login processes.
This master thesis examines if the inertial sensors of a smartphone can be leveraged to continuously determine whether the device is currently in possession of its legitimate owner or by another person. To this end, an approach proposed in related studies will be implemented and examined in detail. This approach is based on the use of a so-called Siamese artificial neural network to transform the measured values of the sensors into a new vector that can be classified more reliably.
It is demonstrated that the reported results of the proposed approach can be reproduced under certain conditions. However, if the same model is used under conditions that are closer to a real-world application, its reliability decreases significantly. Therefore, a variant of the proposed approach is derived whose results are superior to the original model under real conditions.
The thesis concludes with concrete recommendations for further development of the model and provides methodological suggestions for improving the quality of research in the topic of "Continuous Authentication".
Head Mounted Displays (HMD) are increasingly used in various industries. But apart from the industry environment, the potentials of HMDs in a private environment like at home has been rel- atively unexplored so far. What daily tasks can these help with, in the home kitchen for example?
The aim of this thesis is to obtain knowledge about the usefulness of such an HMD, the HoloLens, in combination with an application, while following a new recipe. Therefore a prototype applica- tion for the HoloLens got developed which guides a user through the cooking of a sushi burger by using multimedia content.
With a mixed method design, consisting of quantitative and qualitative methods, the HoloLens in combination with an application was evaluated by 14 participants.
Not only the weight of the device was a problem for users. The test also revealed that the display is darkening the view and participants tend to look below the glasses. An advantage is indeed to reach the next cooking step without the need of using hands and always having in sight what needs to be done next. Positive feedback was given as well for the application. Through voice control the user communicates to a character which will guide through the recipe by videos and text.
If in future the technical characteristics of HMD devices will improve, an application in this con- text will be of advantage in order to simplify learning a new recipe. This device, in combination with an application, could help early-middle stage cognitive impaired people and blind people to cook.
Massively Multiplayer Online Games (MMOGs) are increasing in both popularity and scale.
One of the reasons for this is that interacting with human counterparts is typically considered much more interesting than playing against an Artificial Intelligence.
Although the visual quality of game worlds has increased over the past years,they often fall short in providing consistency with regard to behavior and interactivity.
This is especially true for the game worlds of MMOGs. One way of making a game world feel more alive is to implement a Fire Propagation System that defines show fire spreads in the game world. Singleplayer games like Far Cry 2 and The Legend of Zelda:
Breath of the Wild already feature implementations of such a system. As far as the author of this thesis knows, however, noMMOGwith an implemented Fire Propagation System has been released yet. This work introduces two approaches for developing such a system for a MMOG with a client-server architecture.
It was implemented using the proprietary game engine Snowdrop. The approaches presented in this thesis can be used as a basis for developing a Fire Propagation System and can be adjusted easily to fit the needs of a specific project.
Large-scale computing platforms, like the IBM System z mainframe, are often administrated in an out-of-band manner, with a large portion of the systems management software running on dedicated servers which cause extra hardware costs. Splitting up systems management applications into smaller services and spreading them over the platform itself likewise is an approach that potentially helps with increasing the utilization of platform-internal resources, while at the same time lowering the need for external server hardware, which would reduce the extra costs significantly. However, with regard to IBM System z, this raises the general question how a great number of critical services can be run and managed reliably on a heterogeneous computing landscape, as out-of-band servers and internal processor modules do not share the same processor architecture.
In this thesis, we introduce our prototypical design of a microservice infrastructure for multi-architecture environments, which we completely built upon preexisting open source projects and features they already bring along. We present how scheduling of services according to application-specific requirements and particularities can be achieved in a way that offers maximum transparency and comfort for platform operators and users.
Nowadays more and more companies use agile software development to build software in short release cycles. Monolithic applications are split into microservices, which can independently be maintained and deployed by agile teams. Modern platforms like Docker support this process. Docker offers services to containerize such services and orchestrate them in a container cluster. A software supply chain is the umbrella term for the process of developing, automated building and testing, as well as deploying a complete application. By combining a software supply chain and Docker, those processes can be automated in standardized environments. Since Docker is a young technology and software supply chains are critical processes in organizations, security needs to be reviewed. In this work a software supply chain based on Docker is built and a threat modeling process is used to assess its security. The main components are modeled and threats are identified using STRIDE. Afterwards risks are calculated and methods to secure the software supply chain based on security objectives confidentiality, integrity and availability are discussed. As a result, some components require special treatments in security context since they have a high residual risk of being targeted by an attacker. This work can be used as basis to build and secure the main components of a software supply chain. However additional components such as logging, monitoring as well as integration into existing business processes need to be reviewed.