Quality of Experience and Quality of Service of Gaming Services in Fog Computing

Madiha, Hina; Lei, Lihui; Laghari, Asif Ali; Karim, Sajida

doi:10.1145/3380625.3380644

Cited by 16 publications

(8 citation statements)

References 20 publications

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“…In this research, measurements were made of resource usage, quality of service (QoS) [21] and frame usage which showed how well the test game ran on the virtual machine (VM), and what impact the VM had on the user's laptop if the game load was handled by the cloud server. For QoS parameters taken from 3 different categories, namely network delay, jitter, and throughput [22]. Measurement is carried out in each game with a duration of 1,800 seconds with data sampling every 180 seconds for resource and QoS parameter.…”

Section: Methodsmentioning

confidence: 99%

Cloud server design for heavy workload gaming computing with Google cloud platform

Wicaksono

Munadi

Sussi

2023

IJECE

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Cloud servers are generally used for data storage and remote office activities, but it can be applied for gaming purposes, where cloud servers can be paired with virtual machines and gaming platform that can be accessed by users via an internet connection. This makes the device used by user no longer needs to process resources because the workload is carried out by virtual machines on cloud server. The author designs a cloud gaming system using Google cloud platform as a cloud server and parsec as an optimizer that is attached to a virtual machine for game computing purposes. Author takes measurements of the cloud gaming system using 2 test games varying from low to middle specifications. Resource testing on central processing unit (CPU) and random-access memory (RAM) usage on the user side is below 40% when running game 1 and below 44% when running game 2, while on the system it reaches a capacity above 40% for CPU and RAM and 99% maximum on graphics processing unit (GPU). Quality of service testing of the system is carried out at bandwidths of 5, 10, and 30 Mbps with a minimum bandwidth of 10 Mbps. In general, there are a little difference that occurred between test game and different bandwidths.

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Section: Methodsmentioning

confidence: 99%

Cloud server design for heavy workload gaming computing with Google cloud platform

Wicaksono

Munadi

Sussi

2023

IJECE

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“…To mitigate these risks, device security should be a top priority, with measures such as secure boot, device management, and encryption implemented. 67,68 • Network security: The fog computing network is susceptible to a range of network security threats, including man-in-the-middle attacks, denial-of-service attacks, and unauthorized access. To mitigate these risks, network security measures, such as firewalls, intrusion detection systems, and virtual private networks, should be employed.…”

Section: Security Threats In Fog Computingmentioning

confidence: 99%

“…Some of the most significant security threats in fog computing include: Device security: The devices that make up the fog computing network are vulnerable to various forms of attack, including malware, hacking, and unauthorized access. To mitigate these risks, device security should be a top priority, with measures such as secure boot, device management, and encryption implemented 67,68 Network security: The fog computing network is susceptible to a range of network security threats, including man‐in‐the‐middle attacks, denial‐of‐service attacks, and unauthorized access.…”

Section: Security Threats In Fog Computingmentioning

confidence: 99%

Fog computing security: A review

Jumani

Shi

Laghari

et al. 2023

Security and Privacy

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Fog computing, also known as edge computing, is a decentralized computing architecture that brings computing and data storage closer to the users and devices that need it. It offers several advantages over traditional cloud computing, such as lower latency, improved reliability, and enhanced security. As the Internet of Things continues to grow, the demand for fog computing is also increasing, making it an important topic for research and development. However, the deployment of fog computing also brings new technical challenges and security risks. For example, fog nodes are often deployed in resource‐constrained environments and are exposed to potential security threats, such as malware and attacks on devices connected to the network. In addition, the decentralized nature of fog computing creates new challenges in terms of privacy, security, and data management. This survey aims to address these technical challenges and research gaps in the field of fog computing security. It provides an overview of the current state of fog computing and its security challenges, and identifies key areas for future research. The survey also highlights the importance of fog computing security and the need for continued investment in this area in order to fully realize the potential of this promising technology.

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“…By structure, Fog computing is potentially viable to inject QoS/QoE guarantees by providing local accesses to the users rather than communicating every time to the Cloud. In literature, various issues like energy-efficient design, latency, and minimizing congestion as a whole are explored in a reactive (as and when demand comes) or a proactive (in hindsight) manner in general [21,28,29] or considering particular application in mind [30,31].…”

Section: Related Workmentioning

confidence: 99%

Matching IoT Devices to the Fog Service Providers: A Mechanism Design Perspective

Bandyopadhyay

Singh

Mukhopadhyay

et al. 2020

Sensors

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In the Internet of Things (IoT) + Fog + Cloud architecture, with the unprecedented growth of IoT devices, one of the challenging issues that needs to be tackled is to allocate Fog service providers (FSPs) to IoT devices, especially in a game-theoretic environment. Here, the issue of allocation of FSPs to the IoT devices is sifted with game-theoretic idea so that utility maximizing agents may be benign. In this scenario, we have multiple IoT devices and multiple FSPs, and the IoT devices give preference ordering over the subset of FSPs. Given such a scenario, the goal is to allocate at most one FSP to each of the IoT devices. We propose mechanisms based on the theory of mechanism design without money to allocate FSPs to the IoT devices. The proposed mechanisms have been designed in a flexible manner to address the long and short duration access of the FSPs to the IoT devices. For analytical results, we have proved the economic robustness, and probabilistic analyses have been carried out for allocation of IoT devices to the FSPs. In simulation, mechanism efficiency is laid out under different scenarios with an implementation in Python.

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Quality of Experience and Quality of Service of Gaming Services in Fog Computing

Cited by 16 publications

References 20 publications

Cloud server design for heavy workload gaming computing with Google cloud platform

Cloud server design for heavy workload gaming computing with Google cloud platform

Fog computing security: A review

Matching IoT Devices to the Fog Service Providers: A Mechanism Design Perspective

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