Cloud Data

Cloud Computing For Gaming

Cloud Computing For Gaming – There is no doubt that the cloud will expand access to AAA gaming and significantly increase the total number of players worldwide. In many ways, we can see cloud gaming as the democratization of video games. You no longer need an expensive PC or even a console like Sony PlayStation to play the best games. Instead, the game runs on a powerful computer somewhere else and you stream the vision to your own device – it’s as if your processor is somewhere else.

Aside from the obvious benefit to the casual gaming segment, a common comment among industry observers is that cloud gaming like Google Stadia is also the future of eSports. Contrary to this comment, the truth is that cloud gaming has no direct application to competitive gaming.

Cloud Computing For Gaming

Cloud Computing For Gaming

Before I get into explaining why this is, here’s an analogy to set the scene: A Formula 1 team decided to introduce a new steering wheel. This steering wheel turns the car left and right like all the others, but it does so with a slight delay. Instead of the steering wheel moving and the car reacting immediately, it happens after drivers want it to. This is also not a predictable item – it varies. When they’re going hundreds of miles an hour against people with sharp reflexes, it becomes an extreme disadvantage.

Cloud Gaming System Architecture.

If you’re playing Counter-Strike (or Fortnite) and you press a button, that press is processed in less than 1ms (assuming the USB polling rate is 1000Hz), and if all other hardware delay variables are taken into account, that’s on your screen for about 15-30 milliseconds. We can call it the delay between buttons and pixels. The same can be said for turning the Logitech racing wheel in your favorite racing simulator like iRacing (or Gran Turismo).

When you play these games through a cloud service, your physical input is no longer just a local process. Instead, your input is first sent to a remote server. In order for you to see the input displayed on the screen, it must be processed remotely and sent back via the video stream. If this method of calculation is applied to the desktop, imagine that you are now moving the mouse, but the cursor on the screen will move a little later, not immediately.

This additional delay is added to the existing button-to-pixel delay of 15-30 milliseconds that occurs on the local computer. The entire round trip of this process, from local input to remote rendering and then returning your input to the screen, results in a delay of 60-120 milliseconds.

This puts you at a ~4x disadvantage in great scenarios where the cloud server you’re connecting to is nearby, but it’s often a much bigger disadvantage. In addition, this degree of delay is visually obvious. While the processing of input data on a local computer looks instantaneous, it now looks like a delay when using a cloud service.

Ai & Cloud Computing: Revolutionizing Online Gaming

This delay is the difference between winning and losing. It makes the difference between hitting a perfect corner apex or hitting a wall. It’s the difference between being the first to shoot or being the first to die. According to the laws of physics, with the possible exception of mastering quantum entanglement, there is no scenario where sending data for processing remotely and receiving the results locally could be as fast as simply processing locally.

While these minor delays between pressing a button and seeing the result aren’t a deal-breaker for on-screen single-player, they’re a deal-breaker for single-player in VR, where such delays are annoying. In eSports, these delays are inevitably a competitive disadvantage.

When considering the detrimental effects of cloud gaming on eSports, it’s important to understand that the human ability to react faster is a big part of what separates the elite from everyone else. From network configuration to monitor selection, competitive gamers spend countless hours and large sums of money optimizing latency and improving response time. In the game of thumbs, everything you use to play matters. Just like in F1, it doesn’t matter how good a driver you are if you drive a worse car. In order to offer on-demand game services to many players using heterogeneous client computers, including game consoles, desktops, laptops, smartphones and set-top boxes, more and more service providers are moving PC games to powerful cloud servers and streaming game streams. into a simple application that runs on client computers[2]. Such on-demand game services are called

Cloud Computing For Gaming

From various companies such as Gaikai, Ubitus and OnLive. Market research predicts that the cloud gaming market will grow to $8 billion by 2017 [3] and some leading game development companies [4] are seriously considering this new opportunity. So we expect to see many more cloud gaming services coming soon.

The Cloud Gaming Ecosystem Diagram 2023 Is Here

However, offering cloud gaming services in a commercially viable manner is very difficult, as evidenced by the financial difficulties of OnLive[5]. The main challenge for cloud game providers is to find the best compromise between two conflicting goals:

. Satisfying the game’s QoE requirements for high-end hardware that can bear a huge financial burden; at the same time, the use of low-end hardware leads to a less pleasant QoE for games, which can turn players away from cloud gaming services. Additionally, different game genres have different hardware requirements, which can lead to insufficient or wasted hardware resources if server resources are not properly planned. For example, servers configured for advanced 3D first-person shooters may be overkill for casual 2D games. The variety of servers creates a dilemma to find the best compromise between them

Provides dynamic resource allocation between game servers serving multiple players to improve overall performance and reduce operating costs. In this paper, we investigate the problem of efficient consolidation of multiple cloud game servers on a physical machine using modern virtual machines (VMs) such as VMware and VirtualBox to provide high QoE in games in a cost-effective manner, as shown in Fig. . We solve the VM placement problem to maximize total revenue while providing reasonably good QoE to players. This problem is called

The considered problem is a variant of the virtual network embedding problem [6] and is therefore NP-complete. However, existing solutions for grid-embedded problems [7, 8, 9, 10, 6] are designed for computationally/storage-intensive applications without

How Much Data Does Cloud Gaming Use?

Requirements of cloud games (and other highly interactive applications). In particular, unlike computational/storage-intensive applications that require large CPU/disk bandwidth, cloud games require high QoE, for example, in terms of responsiveness, accuracy, and fairness [ 11 , 12 , 13 ]. Existing virtual network embedding algorithms therefore do

Work for cloud game providers. To the best of our knowledge, this paper is the first attempt to solve the VM placement problem to maximize QoE in cloud gaming.

2.1 General Cloud Applications The optimization of general cloud applications has been investigated in cloud environments. For example, Zaman et al.[15] propose an auction-based mechanism for dynamically provisioning and allocating virtual machines to maximize the provider’s profit and improve the overall utilization of cloud resources. Lin et al. [16] formulated the cloud data replication problem as a mathematical optimization problem and proposed several algorithms for I/O intensive applications. In our work, we formulate the problem of placing a virtual machine in cloud gaming systems and propose optimization algorithms to solve it. Unlike these two studies [15, 16], we optimize real-time cloud games to maximize the provider’s profit using QoE-enabled algorithms while optimizing game quality.

Cloud Computing For Gaming

VM migration techniques have been explored for non-real-time applications. Marzola et al.[17] use live migration technology to move virtual machines away from lightly loaded physical servers so that empty servers can be switched to low-power mode. Ferretta and others. [18] to create a dynamic server consolidation algorithm with migration control and avoid unnecessary migrations to reduce the number of servers involved and migration costs. Chen et al. [19] found that virtual machines usually do not use all their resources and create an algorithm that also considers migration costs according to migration history records to save energy. Speitkamp and Bichler [20] present a heuristic solution that approximates the optimal solution not only by considering costs, but also by determining whether the problem size can be optimally solved. Nathuji et al. [21] build a performance bottleneck model and classify applications under different resource limits using historical data. Applications are then consolidated on physical servers to improve quality of service (QoS). Zhu and Tung[22] also consider obstacles and implement a system to determine the location of virtual machines to avoid obstacles and meet QoS requirements. None of the above studies consider the QoE level of cloud games.

Predictive Cloud Gaming

2.2 Cloud Gaming The benefits of consolidating game servers have been explored for specific game genres. For example, Li and Chen [23] address the problem of server consolidation for massively multiplayer online role-playing games (MMORPGs). In particular, they propose a zone algorithm for the use of spatial location

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