Game Server Research Articles

The Popularity of Faerlina US - World of Warcraft Classic Server: Game Study Using Qualitative Research Methods on the World of Warcraft Classic Game Server

This research discusses the popularity of Faerlina US which is one of the game server of the game World of Warcraft Classic (WoW Classic), a MMORPG (Massively Multiplayer Online Role Playing Game) game version which is one of the World of Warcraft game version released on 26 August 2019. This study uses several qualitative research methods, namely participatory observation, in-depth interviews, and studies of previous studies. The results of this study indicate that the popularity of Faerlina US tends to be driven by the popularity of twitch.tv streamers who play on these servers. This research also shows that Faerlina has also become popular because it is interesting to be a place to conduct economic activities such as selling virtual items and conducting gold-virtual currency transactions into real money.

A load balancing scheme for gaming server applying reinforcement learning in IoT

A lot of data generated on the game server causes overtime in IoT environment. Recently, both researchers and developers have developed great interests in load balancing schemes in gaming servers. The existing literature have proposed algorithms that distribute loads in servers by mostly concentrating on load balancing and cooperative offloading in Internt of Things (IoT) environment. The dynamic load balancing algorithms have applied a technique of calculating the workload of the network and dynamically allocating the workload according to the network situation, taking into account the capacity of the servers. However, the various previous researches proposed are difficult to reflect the real world by imposing a lot of restrictions and assumptions on the IoT environment, and it is not enough to meet the wide range of service requirements for the IoT environment. Therefore, we proposed an agent that applies a deep reinforced learning method to distribute loads for gaming servers. The agent has accomplished this by measuring network loads and analyzing a large amount of user data. We specifically have chosen deep reinforcement learning because no labels would need to be obtained in advance and it enabled our agent to immediately make the right decisions to load balancing in IoT environment. We have showed several siginicicant functions of our proposed scheme and derived through mathematical analysis. Also, we have compared performances of our proposed scheme and a previus research, ProGreGA, widely used scheme through simulation.

Boosted Metaheuristic Algorithms for QoE-Aware Server Selection in Multiplayer Cloud Gaming

Cloud Gaming (CG) provides a high performance and cost-effective solution where players with low-end devices can play high-end games without the need for advanced hardware. A cloud-based video game system offloads all the computational tasks to the cloud. Considering the dynamic nature of game workloads and resource capacity, resource management is still a significant challenge. Since CG is a real-time gaming service, graphics processing units (GPUs) are necessary to accelerate game scene rendering. GPUs are one of the most expensive resources in a CG platform. Therefore, service providers have a strong incentive to utilize GPUs efficiently to maximize their economic profit. In addition, players' quality of game experience (QoE) is a crucial parameter that can directly affect a service provider's profit and must be taken into account in any resource scheduling optimization. To satisfy both parties, in this paper we propose two efficient methods for GPU based server selection in CG. The proposed methods are an improved version of two well-known metaheuristic algorithms called Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), which we refer to as Boosted-PSO and Boosted-GA, respectively. The proposed methods consider service providers' profits and players' experience simultaneously. Our objective is to maximize GPU utilization, which will not only lead to the service provider's economic benefit, but also increase the player's QoE. Our simulation results show that compared to the existing methods to solve such an NP-Hard optimization problem, our Boosted-PSO method, followed by Boosted-GA, achieves the highest efficiency in terms of GPU utilization, capacity wastage, and player's QoE.

Game as a Marketing Tool of Library

As a valuable means to attract users, there are not many game service cases in China, and only a few of previous studies on game program as marketing tools. Based on the method of literature research, we studied several cases and try to analyze how American libraries use game program to marketing themselves at three levels, in order to provide some advice for libraries that need to reach more patrons.

How American Library Put an End to the Low Recognition of Game in Library

Though we already have several successful instances on gaming in library of China, powerful subjective reasons prohibited the development of game services since publicity, librarians and parents taking games as monsters. Also, public have no awareness of the game’s educational and social value. As a result, it is difficult to use game in entertainment, reading program and information literacy instruction. On the contrary, Libraries in US set up professional game librarians and consultants, and the game activities are in full swing. So it is quite necessary to analyze how they gradually overcome the prejudice and popularize game in library. And in this paper we will discuss the following factors: Service traditions, literacy, Library associations,education of future librarian.

Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

Dynamic Service Placement for Virtual Reality Group Gaming on Mobile Edge Cloudlets

To realize mobile virtual reality (VR) group gaming services which are currently hampered by the prohibitive bandwidth and the stringent delay requirements, we investigate the problem of provisioning such services using the emerging mobile edge cloudlet (MEC) networks with a distributed content rendering architecture. The underlying dynamic rendering-module placement problem requires to optimize the service’s operational cost and the users’ end-to-end performance, involving multiple intertwined conflicting system objectives that are discrete, nonconvex, and higher degree polynomial functions with coupled decisions and arbitrary user dynamics over time. We solve this online placement problem by leveraging model predictive control (MPC) and overcoming the aforementioned challenges over each prediction window. We explore the connection between the placement problem and the minimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$s$ </tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> cut problem in graph theory and solve the former via solving a series of instances of the latter. We formally prove the performance guarantee of our approach. We also conduct extensive trace-driven evaluations and demonstrate the superior practical performance of our MPC-based approach compared to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">de facto</i> practices and the state-of-the-art alternatives.

중국 온라인게임 환경에서 게임 서비스 품질, 고객만족, 고객충성도 간의 실증 분석: 이용자 특성의 조절효과

중국 온라인게임 환경에서 게임 서비스 품질, 고객만족, 고객충성도 간의 실증 분석: 이용자 특성의 조절효과

Temporal Mobility Networks in Online Gaming.

This data-driven study focuses on characterizing and predicting mobility of players between gaming servers in two popular online games, Team Fortress 2 and Counter Strike: Global Offensive. Understanding these patterns of mobility between gaming servers is important for addressing challenges related to scaling popular online platforms, such as server provisioning, traffic redirection in case of server failure, and game promotion. In this study, we build predictive models for the growth and the pace of player mobility between gaming servers. We show that the most influential factors in predicting the pace and growth of migration are related to the number of in-game interactions. Declared friendship relationships in the online social network, on the other hand, have no effect on predicting mobility patterns.

Economic impact of energy saving techniques in cloud server

In recent years, lot of research has been carried in the field of cloud computing and distributed systems to investigate and understand their performance. Economic impact of energy consumption is of major concern for major companies. Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain. Demand for energy consumption is increasing day by day in IT firms. Therefore, Cloud Computing companies face challenges towards the economic impact in terms of power costs. Energy consumption is dependent upon several factors, e.g., service level agreement, virtual machine selection techniques, optimization policies, workload types etc. We address a solution for the energy saving problem by enabling dynamic voltage and frequency scaling technique for gaming data centers. The dynamic voltage and frequency scaling technique is compared against non-power aware and static threshold detection techniques. This helps service providers to meet the quality of service and quality of experience constraints by meeting service level agreements. The CloudSim platform is used for implementation of the scenario in which game traces are used as a workload for testing the technique. Selection of better techniques can help gaming servers to save energy cost and maintain a better quality of service for users placed globally. The novelty of the work provides an opportunity to investigate which technique behaves better, i.e., dynamic, static or non-power aware. The results demonstrate that less energy is consumed by implementing a dynamic voltage and frequency approach in comparison with static threshold consolidation or non-power aware technique. Therefore, more economical quality of services could be provided to the end users.

U-실버세대를 위한 스마트 웨어러블 및 연동 게임의 서비스 디자인 방안 탐색: 개인 맞춤형 운동처방 실행을 위한 흥미 유도 목적의 U-Hospital 솔루션

U-실버세대를 위한 스마트 웨어러블 및 연동 게임의 서비스 디자인 방안 탐색: 개인 맞춤형 운동처방 실행을 위한 흥미 유도 목적의 U-Hospital 솔루션

Modelling and transposition of location-based games

Design and development of Location-Based Games (LBG) are not trivial tasks due to their pervasive nature, multidisciplinary requirements, and global deployment issues. This paper presents a model-based approach to describe and generate LBGs. Our approach separates location data, game mechanics, and media content from the game implementation. We aim at allowing LBGs to be edited and deployed in many places quickly. The core is LeGaL, an extension of NCL (Nested Context Language) that models and represents the game structure and its multimedia contents (e.g., video, 3D objects). Its novel approach allows the modelling of mission-based games by supporting relationships between game elements and multimedia documents. We also present a transposition method that provides for LBGs to be deployed around distinct cities in the world by generating balanced game maps. To validate this approach, we applied map balancing measurements to compare the transposed map of an LBG. Additionally, we implemented an authoring tool and a game server that enabled us to model, generate, and to map LBGs. We assessed LeGaL using a qualitative evaluation with six NCL developers. Positive results indicate that our model-based approach has the potential to improve the design and development of LBGs.

Do perceived use contexts influence usage behavior? An instrument development of perceived use context

In this study, we advance current knowledge on IS usage behavior by introducing the concepts of time, location, social, and technological use in perceived use context. We develop an instrument to verify the effects of use context on intention-to-use game services. We find that contextual factors of perceived use context (i.e., perceived time use, perceived location use, perceived social use, and perceived technological use) influence users’ behavioral beliefs (i.e., perceived usefulness and perceived ease of use), which leads to their subsequent attitude and behavioral intention toward using game services. Grounded in our findings, key implications for theory and practice are discussed.

Implementing Mobile Games into Care Services—Service Models for Finnish and Chinese Elderly Care

The purpose of this paper was to create service models for cognitively stimulating mobile games and incorporate them into Finnish and Chinese elderly care. The implementation involved the use of two different mobile games as part of the everyday lives of older adults in care homes in Finland (3 months) and China (6 months). Although a large number of publications examine serious games in elderly care, there are rather few publications related to the practical implementation within the elderly care processes. In general, rehabilitation orientated games should incorporate entertainment (motivation) and relevant therapeutic content (rehabilitation) in order to be effective. Regardless of the game design, successful implementation of the games in elderly care is paramount to benefit the end user. In this paper, two mobile games were investigated as a case study. To investigate the therapeutic content of the games, the game outcomes (game scores and time stamps) were automatically recorded to facilitate analysis of the participant’s progress during the trial. To investigate motivation, user feedback was collected through observation of the game trials and by interviewing the nursing staff and the participants (test group). The gaming service implementation was designed in collaboration with the nursing staff and researchers, according to an experimentation-driven approach, in which the service model ideas were tested by the professionals before piloting. In both countries, the players and the nursing staff found the games showed potential as self-managed rehabilitation tools. Other significant effects of gameplay were enhanced recreation and self-managed activity level. Despite cultural differences, the gaming experience was amazingly similar and improvements in game scores were also observed during the trial in both countries. The biggest difference between the pilots was the implementation process, which led to the development of two different service models that are reported in this paper. In Finland, the games were embedded into the care practices and the nursing staff were responsible for the piloting. In China, the games were independent of the care process and an external service provider (the researcher) managed the piloting. The findings imply that service design in different cultures should be carefully considered when implementing new digital services.

No-Reference Video Quality Estimation Based on Machine Learning for Passive Gaming Video Streaming Applications

Recent years have seen increasing growth and popularity of gaming services, both interactive and passive. While interactive gaming video streaming applications have received much attention, passive gaming video streaming, in-spite of its huge success and growth in recent years, has seen much less interest from the research community. For the continued growth of such services in the future, it is imperative that the end user gaming quality of experience (QoE) is estimated so that it can be controlled and maximized to ensure user acceptance. Previous quality assessment studies have shown not so satisfactory performance of existing No-reference (NR) video quality assessment (VQA) metrics. Also, due to the inherent nature and different requirements of gaming video streaming applications, as well as the fact that gaming videos are perceived differently from non-gaming content (as they are usually computer generated and contain artificial/synthetic content), there is a need for application-specific light-weight, no-reference gaming video quality prediction models. In this paper, we present two NR machine learning-based quality estimation models for gaming video streaming, NR-GVSQI, and NR-GVSQE, using NR features, such as bitrate, resolution, and temporal information. We evaluate their performance on different gaming video datasets and show that the proposed models outperform the current state-of-the-art no-reference metrics, while also reaching a prediction accuracy comparable to the best known full reference metric.

Cost-Efficient and Quality of Experience-Aware Provisioning of Virtual Machines for Multiplayer Cloud Gaming in Geographically Distributed Data Centers

Prompted by the remarkable progress in both cloud computing and GPU virtualization, cloud gaming has become increasingly more popular in the gaming industry. In cloud gaming, games are stored and run on cloud servers and the gamers interact with games through thin clients. Cloud gaming service providers generally employ multiple geographically distributed data centers to deliver their services. The main challenge for cloud gaming service providers is to find the best tradeoff between two contradicting objectives: reducing the infrastructure operating costs and increasing the quality of player's experience. In this paper, we address a virtual machine provisioning problem for multiplayer cloud gaming with the objective of minimizing both the inter-player delay among interacting players and the electricity costs of cloud gaming service providers, while providing the good-enough response delay to gamers. We formulate the problem into a constrained multiobjective optimization problem and propose an improved grey wolf algorithm to solve the problem. The performance of our proposed algorithm are assessed by simulation experiments based on the real-world parameters. The results show the superior performance of the proposed approach in comparison with the state-of-the-art approaches applied to similar problems.

IN-APP PURCHASE SYSTEM BASED ON AUGMENTED REALITY TECHNOLOGY:A CASE STUDY IN HEROES OF SURABAYA MOBILE GAMES

The way on selling software applications today is much changed. Among all of the changes, it is the IAP (In-App Purchase) method for freemium software where users can download and use the application for free but there is a premium feature to be paid. This payment method is believed to be more effective to attract consumers than the payment / purchase made at the beginning by the consumer.When the app developer uses the app's sales option that is an “in-app purchase” then the potential profit or revenuewill be greater because the app-developer may get the revenue many times from one user. Unlike paid-apps where app developers typically only get one-timerevenue from one user for each app they have sold.Some problems with in-app purchase system in mobile games is when choosing the type of payment media for buying items as well as when making a payment when an interruption occurs in the mobile game server that played.Wepropose a solution to this problem by applying Augmented Reality technology to “in-app purchase system” so the system no longer requires internet connection to the game server so users easier for making purchases.This application is made for android smartphone, by combining the in-app purchase system of mobile games heroes of Surabaya with augmented reality using game engine unity and library ARSDK Fuvoria. With augmented reality the app can recognize markers and interact with 3D objects from markers, as well as purchase items from scanned markers. This application can be an alternative solution for purchasing premium items that must be paid using digital money that not everyone understands and have payment media, so smartphone users who want to buy premium items in mobile games only need to buy marker card to make purchases of items to be purchased in mobile games heroes of Surabaya. From the experimental result, the app is get 96% user satisfaction from an attractive sales innovation, but the speed-performance gets only 35% of the user satisfaction level.The light and distance of markers are the key factor of successful rate in maker detection. Keywords: Augmented Reality, In-App Purchase, Marker, Mobile Game, Payment Method

New solutions for exposing clustered applications deployed in the cloud

Hosting applications in the cloud has become very popular. In this context, automatic application scaling, health checking and bootstrapping required services has never been easier. However, there are some types of services that require direct communication between a server and a client, bypassing the cloud. Popular examples include data grids (distributed caching solutions) and gaming servers. Most of these services use custom network protocols based on TCP or UDP transport, along with client-side load balancing, for optimizing network traffic. Unfortunately, most cloud vendors use HTTP-based reverse proxies and are unable to route custom protocols effectively. The major contribution of this paper is a proposed method for using a single load balancer per application instance (replica) to solve the problem of effective communication between a clustered application deployed within the cloud, and a client hosted in the outside world.

Toward Multiplayer Cooperative Cloud Gaming

Cloud gaming has been attracting increasing attention in the game industry. Nevertheless, the benefits of cloud gaming platforms in facilitating multiplayer games have not been widely discussed in the literature. This article reveals this emerging trend and discusses a supporting network architecture for multiplayer cooperative cloud gaming. The article further examines two existing modalities that adopt cooperation among neighboring players to optimize the quality of service in cloud gaming services.

An asynchronous method for cloud-based rendering

Interactive high-fidelity rendering is still unachievable on many consumer devices. Cloud gaming services have shown promise in delivering interactive graphics beyond the individual capabilities of user devices. However, a number of shortcomings are manifest in these systems: high network bandwidths are required for higher resolutions and input lag due to network fluctuations heavily disrupts user experience. In this paper, we present a scalable solution for interactive high-fidelity graphics based on a distributed rendering pipeline where direct lighting is computed on the client device and indirect lighting in the cloud. The client device keeps a local cache for indirect lighting which is asynchronously updated using an object space representation; this allows us to achieve interactive rates that are unconstrained by network performance for a wide range of display resolutions that are also robust to input lag. Furthermore, in multi-user environments, the computation of indirect lighting is amortised over participating clients.