Multimedia service utilizing hierarchical fog computing for vehicular networks

Kharel, Jeevan; Shin, Soo Young

doi:10.1007/s11042-018-6530-3

Cited by 8 publications

(5 citation statements)

References 25 publications

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“…In 2019, Kharel & Shin, (2019) introduced fog computing to address unstable connections, internet connection speed, bandwidth issues that affect QoS and QoE for multimedia streaming in vehicular networks. Their simulation results based on performance evaluation proved that introducing fog computing can enhance QoS and bring better QoE to users.…”

Section: Related Workmentioning

confidence: 99%

Fog Computing Quality of Experience

Vambe

2023

International Journal of Fog Computing

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Since its inception in 2012, fog computing has played a dominant role in addressing the quality of service (QoS). However, with the emergence of the internet of things and artificial intelligence technologies, which create a “smart world” where everything is automated, offering quality of service alone is no longer sufficient as it does not offer a satisfactory user experience. Quality of experience (QoE), which satisfies user experience and improves user performance, becomes vital and fog computing remains a key technology. To understand QoE, there was a need to distinguish it from QoS based on stance, scope, perspective, focus, and methods. A systematic literature review was done looking at works that use fog computing to maintain or improve QoE with the focus being on problems being addressed in a paper and how the results contributed to improving QoE. Critical analysis of the review showed that even though strides have been made to improve QoE, open research challenges still exist that require intervention to improve or maintain acceptable QoE in fog computing to satisfy user needs.

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Section: Related Workmentioning

confidence: 99%

Fog Computing Quality of Experience

Vambe

2023

International Journal of Fog Computing

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“…A hierarchical FG-based multimedia streaming that reduces latency and minimizes internet bandwidth consumption for passengers traveling in any vehicle is proposed by [27]. The result acquired from the simulation showed that the secondary and primary fog stations located at the edge were considered the better and best-case scenario to allocate multimedia services regarding QoS and QoE.…”

Section: Cloud-fog Hierarchical Environmentsmentioning

confidence: 99%

“…1. Dynamic Adjustment (DA) [27]: The task for serving the client's media request is carried out in a hierarchical manner. 2.…”

Section: Network Traffic Predictionmentioning

confidence: 99%

Multimedia Services Placement Algorithm for Cloud-Fog Hierarchical Environments

Santos,

Immich,

Madeira

2022

Preprint

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With the rapid development of mobile communication, multimedia services have experienced explosive growth in the last few years. The high quantity of mobile users, both consuming and producing these services to and from the Cloud Computing (CC), can outpace the available bandwidth capacity. Fog Computing (FG) presents itself as a solution to improve on this and other issues. With a reduction in network latency, real-time applications benefit from improved response time and greater overall user experience. Taking this into account, the main goal of this work is threefold. Firstly, it is proposed a method to build an environment based on Cloud-Fog Computing (CFC). Secondly, it is designed two models based on Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM). The goal is to predict demand and reserve the nodes' storage capacity to improve the positioning of multimedia services. Later, an algorithm for the multimedia service placement problem which is aware of data traffic prediction is proposed. The goal is to select the minimum number of nodes, considering their hardware capacities for providing multimedia services in such a way that the latency for servicing all the demands is minimized. An evaluation with actual data showed that the proposed algorithm selects the nodes closer to the user to meet their demands. This improves the services delivered to end-users and enhances the deployed network to mitigate provider costs. Moreover, reduce the demand to Cloud allowing turning off servers in the data center not to waste energy.

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“…In fact, there are many nonstandard management, which need to be improved. Statistical data are also prone to errors, and it is also very difficult to share the statistical data and information for the second time [13,14]. Without a unified equipment management system, the information sharing of multimedia teaching equipment is very cumbersome, and even cannot be shared, resulting in information redundancy and junk information.…”

Section: Introductionmentioning

confidence: 99%

Study and Design of Scalable Multimedia Service System

Zhao

2022

Mobile Information Systems

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In recent years, with the continuous advancement of multimedia technology and network technology, network-based multimedia applications are increasing day by day, both in scale and in the number of users. However, the randomness, time-varying, and complexity of user behavior and network make it impossible to guarantee the service quality (bandwidth, delay, etc.) of multimedia services, thus making it difficult to meet the demands of growing users for multimedia services. While meeting the application requirements, how to design and develop a scalable multimedia service system has become one of the key issues to support good multimedia services and better develop multimedia service services. In addition, the surge in user demand comes with various challenges. High-definition and smooth multimedia services require stable bandwidth. However, the randomness, time-varying, and complexity of user behaviors and network states usually make it difficult to guarantee the quality of services. It is of practical significance to study how to overcome these problems, and it is also a hotspot of current research. This paper mainly discusses the extensibility elements of the multimedia service system and puts forward the relationship between the extensibility of various elements and some design principles of the extensibility. In order to overcome the influence of random variation of the wireless channel on video playback, this paper adopts scalable coding technology. That is, through the analysis of the playback process, the underflow probability is proposed and defined, thereby establishing a constrained optimization problem. Finally, this paper also proposes the multimedia adaptive transmission in the network to do the optimization.

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Multimedia service utilizing hierarchical fog computing for vehicular networks

Cited by 8 publications

References 25 publications

Fog Computing Quality of Experience

Fog Computing Quality of Experience

Multimedia Services Placement Algorithm for Cloud-Fog Hierarchical Environments

Study and Design of Scalable Multimedia Service System

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