2 edition of Mst:Evaluting Effective Framework for Provide Efficient Transcode Services found in the catalog.
Mst:Evaluting Effective Framework for Provide Efficient Transcode Services
by Association of Scientists, Developers and Faculties in India
Written in English
The rapidly increasing power of personal mobile devices (smartphones, tablets, etc.) is providing much richer contents and social interactions to users on the move. This trend however is throttled by the limited battery lifetime of mobile devices and unstable wireless connectivity, making the highest possible quality of service experienced by mobile users not feasible. The recent cloud computing technology, with its rich resources to compensate for the limitations of mobile devices and connections, can potentially provide an ideal platform to support the desired mobile services. Tough challenges arise on how to effectively exploit cloud resources to facilitate mobile services, especially those with stringent interaction delay requirements. In this paper, we propose the design of a Cloud-based, novel Mobile sOcial tV system (CloudMoV). The system effectively utilizes both PaaS (Platform-as-a-Service) and IaaS (Infrastructure-asa- Service) cloud services to offer the living-room experience of video watching to a group of disparate mobile users who can interact socially while sharing the video. To guarantee good streaming quality as experienced by the mobile users with timevarying wireless connectivity, we employ a surrogate for each user in the IaaS cloud for video downloading and social exchanges on behalf of the user. The surrogate performs efficient stream transcoding that matches the current connectivity quality of the mobile user. Given the battery life as a key performance bottleneck, we advocate the use of burst transmission from the surrogates to the mobile users, and carefully decide the burst size which can lead to high energy efficiency and streaming quality. Social interactions among the users, in terms of spontaneous textual exchanges, are effectively achieved by efficient designs of data storage with BigTable and dynamic handling of large volumes of concurrent messages in a typical PaaS cloud. These various designs for flexible transcoding capabilities, battery efficiency of mobile devices and spontaneous social interactivity together provide an ideal platform for mobile social TV services. We have implemented Cloud MoV on Amazon EC2 and Google App Engine and verified its superior performance based on real world experiments.
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The rapidly increasing power of personal mobile devices (smartphones, tablets, etc.) is providing much richer contents and social interactions to users on the move.
This trend however is throttled by the limited battery lifetime of mobile devices and. Download Citation | Mst:Evaluting Effective Framework for Provide Efficient Transcode Services | The rapidly increasing power of personal mobile devices (smartphones, tablets, etc.) is providing.
We design and implement a new system framework, Reflex, to provide the required system support to achieve spontaneous social interaction with other users in the same mobile application, be they in. This paper describes a framework architecture for the automated re-purposing and efficient delivery of multimedia content stored in CMSs.
It deploys specifically designed templates as well as adaptation rules based on a hierarchy of profiles to accommodate user, device and network requirements invoked as constraints in the adaptation by: 1. The advantage of this approach is that summarization and adaptation are integrated into the same efficient framework.
The utility of this approach is demonstrated with experimental results for the generation of storyboards and video skims, showing that the proposed framework can generate the adapted bitstream of the summary faster than a conventional transcoding by: These various designs for flexible transcoding capabilities, battery efficiency of mobile devices and spontaneous social interactivity together provide an ideal platform for mobile social TV services.
In this paper, we propose and implement a cloud-based scalable and cost-effective video streaming transcoding service platform to provide the service of changing real-time streaming protocols. In this paper, a coding unit complexity (CUC)-based prediction method for predictions of CU (coding unit) depth and PU (prediction unit) mode for efficient HEVC-to-SHVC transcoding with quality scalability is proposed to significantly reduce the transcoding complexity.
As the next generation networks promise to provide network convergence with services for both static and mobile networks, the recent research focus is converging in the direction of standardizing. To transcode a video, we will use two services of Amazon that are listed below and the work flow shown in the image: Step 1: Upload File at S3 (Simple Storage Service) This service is used to store and retrieve any type of file at Amazon cloud using different types of requests like POST, PUT or GET, that adhere to security policies.
This book is designed to provide the researchers and practitioners with relevant theoretical frameworks and latest technical and institutional solutions for transcoding multimedia in mobile and wireless networks, as well as providing an insight into the field of Multimedia and its associated technologies and communication protocols.
Video transcoding involves heavy computation as well as constant read and write to a disk is required. A p 30 fps video file of MB size encoded using x codec was used as input data and the video was converted to a h mp4 file.
Many multinational companies are trading in spectrum to provide data and voice services over wireless and mobile space. This research paper is a comparison of various network optimization as well as compression technologies for wireless network and mobile network.
A performance model of effective memory management in HYDRA: a large scale data stream recording system Author(s): Kun Fu ; Roger Zimmermann. The real time video transcoding will use novel video coding algorithms such as High Efficiency Video Coding HEVC/H To enable efficient transcoding, significant work will be required in modeling, mapping and optimizing parts of the algorithms to different underlying MANGO architecture elements (tiles), as shown in Fig.
Introduction. Big data analyzing for basic methods such as classification, retrieval, and prediction has become famous for multimedia sources such as text, graphics, images, audio, and video. The MapReduce framework developed by Google is very simple and flexible for various large-scale data processing functions.
This framework is a powerful, efficient tool to develop scalable parallel. Introduction. Cloud computing builds a powerful data center through DCN technology, transmission protocols, and network sharing mechanisms to provide efficiency, low cost, high reliability, and sustainable services, bringing convenience to cloud relies on the powerful resources of cloud computing to provide users with emerging media services.
Interactive live streaming is a key feature of applications and platforms in which the actions of the viewers affect the content of the stream. In those, a minimal capture-display delay is critical. Though recent technological advances have certainly made it possible to provide web-based interactive live-streaming, little research is available that compares the real-world performance of the.
Mumbai (NSE & BSE) – July 2nd – Tata Communications, a leading provider of A New World of Communications, today announces that it has launched the world’s first cloud-based broadcast quality video transcoding and delivery service.
The new content transformation service has already been selected by Viacom18, a joint venture between Viacom Inc. and the Network18 Group, to provide high. Owing to the high compression efficiency improvement of High Efficiency Video Coding (HEVC) standard, it is expected as a successor to H The widely usage of H today and the expected future adoption of HEVC raises a new demand for H to HEVC transcoding.
The focus of this paper is the Performance Efficiency pillar of the Amazon Web Services (AWS) Well-Architected Framework. It provides guidance to help customers apply best practices in the design, delivery, and maintenance of AWS environments.
This whitepaper covers the best practices for managing production environments.scalable, cost effective, high performing content delivery workflow that optimizes the network and infrastructure resources to provide a glitch-free QoE (Quality of Experience).
This unique framework minimizes the go-to-market and operational costs, while ensuring hassle-free deployment and effective .Some players in the mobile computing market with an emphasis on content and services, such as ringtones, music in MP3 format as well as MMS consumer oriented.
However, according to a study by IT research firm, 40 % of companies use wireless technology for business applications bycompared with only 5 % in