Cloud Gaming Services Research Articles

УПРАВЛЕНИЕ КОМАНДОЙ ВНУТРИКОРПОРАТИВНОГО СТАРТАПА: ПРОЦЕССНОЕ ИССЛЕДОВАНИЕ ДИНАМИКИ РАЗВИТИЯ

Innovative development of the Russian economy is impossible without increasing the efficiency of small innovative enterprises (startups), including those created within companies. The problems of managing internal startups and especially startup teams have been relatively poorly studied by modern science. The high dynamics of startups causes high variability and intensive transformations in team management practices. To create a highper formance startup team, it is necessary to understand the internal logic of change in the parameters of teams and team management. The article studies the dynamics of changes in team characteristics and team management within the startup development process. The research methodology is based on process research and case studies. The work investigates the dynamics of the startup team a cloud gaming service. The startup was organized within one company but was then sold to a large IT corporation. The article examines certain characteristics of the team in their development including management methodologies, team composition, communications, culture, motivation, operational and strategic planning pro cedures.

An online cost optimization approach for edge resource provisioning in cloud gaming

Cloud gaming (CG), as an emergent computing paradigm, is revolutionizing the gaming industry. Currently, cloud gaming service providers (CGSPs) begin to integrate edge computing with cloud to provide services, with the aim of maximizing gaming service revenue while considering the costs incurred and the benefits generated. However, it is non-trivial to maximize gaming service revenue, as future requests are not known beforehand, and poor resource provisioning may result in exorbitant costs. In addition, the edge resource provisioning (ERP) problem in CG necessitates a trade-off between cost and inevitable queuing issues in CG systems. To address this issue, we propose ERPOL (ERP Online), a convenient and efficient approach to formulate ERP strategies for CGSPs, without requiring any future information. The performance of ERPOL has been theoretically validated and experimentally evaluated. Experiments driven by real-world traces show that it can achieve significant cost savings. The proposed approach has the potential to transform how CGSPs manage their infrastructure.

Service quality in cloud gaming: instrument development and validation

PurposeThe global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.Design/methodology/approachA three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.FindingsCloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.Practical implicationsPractitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.Originality/valueThis study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

Video Streaming and Cloud Gaming Services Over 4G and 5G: A Complete Network and Service Metrics Dataset

The development of telecommunications, particularly mobile communications, has led to the emergence of numerous multimedia services. As these services become increasingly reliant on connectivity, the network has a huge impact on the user experience. However, it is difficult to assess the End-to- End (E2E) performance of the service because of the limited access to the application data and encryption used to secure and integrate the network information exchanged. In this context, this work presents a dataset based on several metrics, namely Key Quality Indicators (KQIs), representing different services' E2E conditions. In particular, video streaming and Cloud Gaming (CG) services are considered in the dataset. Furthermore, a detailed description of the testbed where the dataset has been generated is given, discussing the rationale behind the choices made for its development.

Future Business Model for Mobile Cloud Gaming: the Case of South Korea and Implications

5G was expected to have a disruptive impact on society owing to its high bandwidth, hyper-connectivity, and low latency. Mobile cloud gaming, therefore, was expected to take off with the introduction of 5G. However, progress has not been successful and it means that factors beyond technological advancement need to be considered. This paper interviews experts to analyze the current status of mobile cloud gaming services to better understand the mobile cloud gaming industry. The findings reaffirm that the performance of the service (e.g., latency, coverage of 5G networks, etc.) is a critical factor, but also reveal the lack of consideration of the polarized user segments and bidirectional requirements of gaming services. Therefore, to facilitate the expansion of mobile cloud gaming, industry and academia alike should focus on transforming the mobile cloud gaming services in two ways. First, provide bundles of casual games with a freemium business model using existing infrastructure. Second, expand coverage of 5G networks and optimize service for ultra-low latency. Since it is more feasible to take the first approach, it is recommended that the initial efforts focus on the first, rather than the second, which frequently has been the case.

Measuring and estimating Key Quality Indicators in Cloud Gaming services

The gaming industry has proposed the concept of Cloud Gaming (CG), a paradigm that enhances the gaming experience on reduced hardware devices. However, this paradigm puts a lot of pressure on the communication links that connect the user to the cloud. As a result, the service experience becomes highly dependent on network connectivity.In this context, the present work proposes a framework for measuring and estimating the most important E2E (end-to-end) metrics of the CG service, namely Key Quality Indicators (KQIs). Therefore, different machine learning (ML) techniques are evaluated to predict KQIs related to the CG user experience. For this purpose, the most important KQIs of the service, such as input lag, freezes or perceived video frame rate, are collected in a real network deployment. The results show that ML techniques can be used to estimate these indicators solely from network-related metrics. This is seen as a valuable asset for the delivery of CG services over cellular networks, even without access to the user’s device, as it is expected for telecom operators.

Legal Regulation of Cloud Gaming

The paper considers the problems of using cloud gaming technology. The author defines cloud gaming and explores three main models according to which remote access to games can be provided: software as a service, a platform as a service, and an infrastructure as a service. The author examines two blocks of issues that arise when using cloud services for games. In particular, taking several cloud gaming services as a case study, the author examines the following issues from the field of intellectual property: communicating to the public and reproducing computer games and contract law regulation of relations between a cloud services’ operator, a player and a rightholder. The paper highlights the legal nature of a relationship between the cloud services’ operator and the player and elements of the corresponding contract. It is concluded that the current legal regulation allows the parties involved to resolve most issues in this area.

E-Render: Enabling UHD-Quality Cloud Gaming Through Edge Rendering

Cloud gaming services enable users to enjoy various high-quality computer games without installing them in their devices which may have poor resources. However, it consumes high bandwidth in backbone networks as game videos have to be constantly streamed to client devices, which can be a hindering factor for providing Ultra High Definition (UHD)-quality cloud gaming services whose demands are ever increasing. In this paper, we present a novel cloud gaming architecture, <i>E-Render</i>, in which the graphics engine is separated from the cloud game server and is deployed in the edge for rendering. In the architecture, since video frames are streamed from the edge server to the client device via highbandwidth subscriber networks, we can greatly save the backbone network bandwidth. To realize it, however, we need to effectively reduce the amount and latency of graphics commands transfer from the game engine in the cloud to the graphics engine in the edge server. E-render solves the problem by using novel techniques including multi-granular command deduplication and asynchronous buffer binding. We implement a prototype cloud gaming platform based on the E-Render architecture, and evaluate its performance using four real world games. The evaluation results confirm that E-Render can provide UHD-quality cloud gaming services.

Cloud Gaming Demystified: An Introduction to the Legal Implications of Cloud-Based Videogames

In this paper, we “demystify” cloud-based videogaming and its legal implications, in two stages. First, we describe the videogame sector; explain the basics of cloud computing and traditional videogame technologies and set out how the two converge in cloud-based videogame systems. Based on this analysis, we distinguish three separate models for cloud gaming services: (i) the “layered” model of Gaming-as-a-Service (‘GaaS’); (ii) the ‘integrated’ model of GaaS; and (iii) the ‘consumer infrastructure-as-a-service’ model. We argue that these three models are key to analyzing how intellectual property rights, contractual rights, and regulatory issues will develop in this novel environment for videogame distribution and access.

A Network Analysis on Cloud Gaming: Stadia, GeForce Now and PSNow

Cloud gaming is a class of services that promises to revolutionize the videogame market. It allows the user to play a videogame with essential equipment while using a remote server for the actual execution. The multimedia content is streamed through the network from the server to the user. Hence, this service requires low latency and a large bandwidth to work properly with low response time and high-definition video. Three of the leading tech companies (Google, Sony, and NVIDIA) entered this market with their products, and others, like Microsoft and Amazon, are also launching their platforms. However, these companies have released little information about their cloud gaming operation and how they utilize the network. In this work, we study cloud gaming services from the network point of view. We collect more than 200 packet traces under different application settings and network conditions from a broadband network to poor mobile network conditions, for 3 cloud gaming services, namely Stadia from Google, GeForce Now from NVIDIA and PS Now from Sony. We analyze the employed protocols and the workload that they impose on the network. We find that GeForce Now and Stadia use the RTP protocol to stream the multimedia content, with the latter relying on the standard WebRTC APIs. Depending on the network and video quality, they result in bandwidth-hungry services consuming up to 45 Mbit/s. PS Now instead uses only undocumented protocols and never exceeds 13 Mbit/s. 4G mobile networks can often sustain these loads, while traditional 3G connections struggle. The systems quickly react to deteriorated network conditions, and packet losses up to 5% do not cause a reduction in resolution.

Increasing Player Performance and Game Experience in High Latency Systems

Cloud gaming services and remote play offer a wide range of advantages but can inherent a considerable delay between input and action also known as latency. Previous work indicates that deep learning algorithms such as artificial neural networks (ANN) are able to compensate for latency. As high latency in video games significantly reduces player performance and game experience, this work investigates if latency can be compensated using ANNs within a live first-person action game. We developed a 3D video game and coupled it with the prediction of an ANN. We trained our network on data of 24 participants who played the game in a first study. We evaluated our system in a second user study with 96 participants. To simulate latency in cloud game streaming services, we added 180 ms latency to the game by buffering user inputs. In the study we predicted latency values of 60 ms, 120 ms and 180 ms. Our results show that players achieve significantly higher scores, substantially more hits per shot and associate the game significantly stronger with a positive affect when supported by our ANN. This work illustrates that high latency systems, such as game streaming services, benefit from utilizing a predictive system.

Server Allocation for Massively Multiplayer Online Cloud Games Using Evolutionary Optimization

In recent years, Massively Multiplayer Online Games (MMOGs) are becoming popular, partially due to their sophisticated graphics and broad virtual world, and cloud gaming is demanded more than ever especially when entertaining with light and portable devices. This article considers the problem of server allocation for running MMOG on cloud, aiming to reduce the cost on cloud gaming service and meanwhile enhance the quality of service. The problem is formulated into minimizing an objective function involving the cost of server rental, the cost of data transfer and the network latency during the gaming time. A genetic algorithm is developed to solve the minimization problem for processing simultaneous server allocation for the players who log into the system at the same time while many existing players are playing the same game. Extensive experiments based on the player behavior in “World of Warcraft” are conducted to evaluate the proposed method and compare with the state-of-the-art as well. The experimental results show that the method gives a lower cost and a shorter network latency in most of the time.

Virtual Machine Placement Optimization in Mobile Cloud Gaming Through QoE-Oriented Resource Competition

Cloud gaming is a novel service provisioning paradigm, which hosts video games in the cloud and transmits interactive game streams to game players via the Internet. In such cloud gaming scenarios, the cloud is required to consume tremendous resources for video rendering and streaming, especially when the number of concurrent players reaches a certain level. On the other hand, different game players may have distinct requirements on Quality-of-Experience, such as high video quality, low delay, etc. Under this circumstance, how to satisfy players of different interests by efficiently leveraging cloud resources becomes a major challenge to existing cloud gaming services. In order to meet the overall requirements of players in a cost-effective manner, this article applies game theory to cloud gaming scenarios. It proposes a distributed algorithm to optimize virtual machine (VM) placement in mobile cloud gaming through resource competition. Further, by constructing a potential function, we prove that the resource competition game is a potential game, and the proposed algorithm scales well as the player population increases. We prove theoretically and verify experimentally that, with the proposed distributed VM placement algorithm, players can achieve a mutually satisfying state within a finite number of iterations.

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.

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.

Cost-Efficient Server Provisioning for Cloud Gaming

Cloud gaming has gained significant popularity recently due to many important benefits such as removal of device constraints, instant-on, and cross-platform. The properties of intensive resource demands and dynamic workloads make cloud gaming appropriate to be supported by an elastic cloud platform. Facing a large user population, a fundamental problem is how to provide satisfactory cloud gaming service at modest cost. We observe that the software storage cost could be substantial compared to the server running cost in cloud gaming using elastic cloud resources. Therefore, in this article, we address the server provisioning problem for cloud gaming to optimize both the server running cost and the software storage cost. We find that the distribution of game software among servers and the selection of server types both trigger tradeoffs between the software storage cost and the server running cost in cloud gaming. We formulate the problem with a stochastic model and employ queueing theory to conduct a solid theoretical analysis of the system behaviors under different request dispatching policies. We then propose several classes of algorithms to approximate the optimal solution. The proposed algorithms are evaluated by extensive experiments using real-world parameters. The results show that the proposed Ordered and Genetic algorithms are computationally efficient, nearly cost-optimal, and highly robust to dynamic changes.

A Hybrid-Streaming Method for Cloud Gaming: To Improve the Graphics Quality delivered on Highly Accessible Game Contents

The emerging Cloud Gaming Service provides a highly accessible video gaming experience. With Cloud Gaming, potential players without enough local resource can access high-quality gaming using low-spec devices. With advancing technology, we consider that if the processing power at low-spec devices can be well harvested, the quality delivered on Cloud Gaming can be further improved. Therefore, we propose a Hybrid-Streaming System that aimed at improving the graphic quality delivered by Cloud Gaming. By utilizing the available rendering power from both the Cloud Server and client PC, the system distributes rendering operations to both sides to achieve the desired improvement. Quantitative results show the proposed method improves graphics quality, as well as reducing the server’s workload while attaining acceptable network bandwidth consumption levels.

Toward Delay-Efficient Game-Aware Data Centers for Cloud Gaming

Gaming on demand is an emerging service that has recently started to garner prominence in the gaming industry. Cloud-based video games provide affordable, flexible, and high-performance solutions for end-users with constrained computing resources and enables them to play high-end graphic games on low-end thin clients. Despite its advantages, cloud gaming's Quality of Experience (QoE) suffers from high and varying end-to-end delay. Since the significant part of computational processing, including game rendering and video compression, is performed in data centers, controlling the transfer of information within the cloud has an important impact on the quality of cloud gaming services. In this article, a novel method for minimizing the end-to-end latency within a cloud gaming data center is proposed. We formulate an optimization problem for reducing delay, and propose a Lagrangian Relaxation (LR) time-efficient heuristic algorithm as a practical solution. Simulation results indicate that the heuristic method can provide close-to-optimal solutions. Also, the proposed model reduces end-to-end delay and delay variation by almost 11% and 13.5%, respectively, and outperforms the existing server-centric and network-centric models. As a byproduct, our proposed method also achieves better fairness among multiple competing players by almost 45%, on average, in comparison with existing methods.

The Future of Cloud Gaming [Point of View

Examines the future for cloud gaming services. These services have leveraged real-time video streaming technologies that have a long history of development. Cloud gaming refers to the technologies that offload parts of game software from traditional game consoles or personal computers (PCs) to powerful and elastic cloud infrastructures. Cloud gaming makes perfect sense to: 1) gamers, who otherwise have to constantly upgrade their consoles or PCs, which is certainly no fun and costly; 2) cloud service providers, who can sell the already-deployed and idling cloud resources to support the cutting-edge games that are extremely resource hungry; and 3) game developers, who no longer need to spend months to port their games to different platforms. As such, cloud gaming has attracted significant attention from both academia and industry.