CloudStream: Delivering high-quality streaming videos through a cloud-based SVC proxy

Huang, Zixia; Mei, Chao; Li, Li Erran; Woo, T.Y.C.

doi:10.1109/infcom.2011.5935009

Cited by 129 publications

(52 citation statements)

References 6 publications

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“…S. Heiko et al [18] and W.Mathias et al [19] gave a detailed introduction about the Scalable and Adaptive video coding technologies and working principles. [20]- [22] proposed a model for cloud based video Transcoding services for mobile devices. L.Yao et al [24] measured a server side workload for mobile streaming service provision.…”

Section: Related Workmentioning

confidence: 99%

A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE

Rajasekaran¹,

Keerthiga²

2018

IJCA

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The drastic increase in the usage of handheld devices like smartphones, tablets, etc., produce huge traffic on the Internet which are mainly due the video streaming services applications. Due to the limitations of resources (Power, Memory, Processing, etc.), numerous design patterns of the mobile devices and heterogeneous users' expectations, it is difficult to handle those video streaming services requests. In order to provide an expected experience to the end user and to reduce the burden of the service providers, cloud computing provides the most easy and viable solution. A novel framework in cloud environment has been proposed in this paper to provide a good trade-off between the service handling as well as the user experience. The framework covers various aspects related to streaming services such as user experience, content distribution and retrieval, power usage, network analysis, video storage, device analysis on static and runtime conditions, parallel service provision and the experience perceived by user. General TermsCloud Based Video Streaming Services

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Section: Related Workmentioning

confidence: 99%

A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE

Rajasekaran¹,

Keerthiga²

2018

IJCA

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“…An algorithm was proposed in [12] to choose appropriate cloud providers for improving the quality of service (QoS) of video streaming and reducing the cost to utilize the cloud resources. In [13], the Scalable Video Coding proxy based on cloud computing was proposed that can deliver highquality video streams. An integer programming model was formulated in [4] to allocate virtual machines (VMs) provided by a cloud provider for operating a video surveillance platform.…”

Section: Related Workmentioning

confidence: 99%

Cloud-Based Video Monitoring Framework: An Approach Based on Software-Defined Networking for Addressing Scalability Problems

Sandar

Chaisiri

Yongchareon

et al. 2015

Lecture Notes in Computer Science

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Abstract. Closed-circuit television (CCTV) and Internet protocol (IP) cameras have been applied to a surveillance or monitoring system, from which users can remotely monitor video streams. The system has been employed for many applications such as home surveillance, traffic monitoring, and crime prevention. Currently, cloud computing has been integrated with the video monitoring system for achieving value-added services such as video adjustment, encoding, image/video recognition, and backup services. One of the challenges in this integration is due to the size and geographical scalability problems when video streams are transferred to and retrieved from the cloud services by numerous cameras and users, respectively. Unreliable network connectivity is a major factor that causes the problems. To deal with the scalability problems, this paper proposes a framework designed for a cloud-based video monitoring (CVM) system. In particular, this framework applies two major approaches, namely stream aggregation (SA) and software-defined networking (SDN). The SA approach can reduce the network latency between cameras and cloud services. The SDN approach can achieve the adaptive routing control which improves the network performance. With the SA and SDN approaches applied by the framework, the total latency for transferring video streams can be minimized and the scalability of the CVM system can be significantly enhanced.

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“…Here the former idea pertains to the quality of service(QOS) services for multimedia content and the later concept deals about how well the sharing, retrieval and storage of the multimedia content can utilize the cloud-computing resources for achieving a better Quality Of experience [2] More finer framework like as Cloud Assisted Live Media Streaming have been studied to utilize the cloud resources by leasing and adjusting the cloud servers for the dynamic user demands [15].Basically the video streaming using the cloud technology relies on the transcoding mechanism, which has two mapping options like Hallsh-based and Lateness-first Mapping for reducing the jitter in the transcoding [7]. Also the Scalable Video Coding framework has also been proposed to reduce the latencies in the transcoding and to adapt to the dynamically changing network conditions [3]. The works of Satyanarayanan et al [13] have suggested the implementation of the dynamic virtual machine in carrying out the offloading to the mobile devices computations.…”

Section: Related Workmentioning

confidence: 99%