CLEVER: a cooperative and cross-layer approach to video streaming in HetNets

We investigate the problem of providing a video streaming service to mobile users in an heterogeneous cellular network composed of micro e-NodeBs (eNBs) and macro e-NodeBs (MeNBs). More in detail, we target a cross-layer dynamic allocation of the bandwidth resources available over a set of eNBs and one MeNB, with the goal of reducing the delay per chunk experienced by users. After optimally formulating the problem of minimizing the chunk delay, we detail the Cross LayEr Video stReaming (CLEVER) algorithm, to practically tackle it. CLEVER makes allocation decisions on the basis of information retrieved from the application layer aswell as from lower layers. Results, obtained over two representative case studies, show that CLEVER is able to limit the chunk delay, while also reducing the amount of bandwidth reserved for offloaded users on the MeNB, as well as the number of offloaded users. In addition, we show that CLEVER performs clearly better than two selected reference algorithms, while being very close to a best bound. Finally, we show that our solution is able to achieve high fairness indexes and good levels of Quality of Experience (QoE)

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Mobile Multimedia Streaming Library

In recent years, multimedia has become a commonly used tool for presenting contents to the users. The employment of multimedia is no longer limited to only the entertainment industry, but spans in other areas as well. In academics, lectures are recorded to audio and video for storage and distribution to students. Free online multimedia hosting services are popularly cherished, such as “youtube.com” and “yahoo video”, and with the increasing affordability of digital camera, hundreds, or maybe thousands, of home-made videos and music audio are created daily and published online. Low-cost digital recorders such as webcams also help promote the use of video for surveillance, both for commercial and personal use. Suddenly, there comes the need for digital multimedia delivery, which happens naturally with the advancement in Internet bandwidth and the popularity of multimedia sharing. Multimedia delivery comes in two methods: downloading and streaming. Streaming requires more complex structure, but rewards with better user experience. Although streaming is the method of choice today, downloading is still useful in ad-hoc situation where streaming is not feasible. This project aims to provide streaming-like capability to mobile devices. Since mobile gadgets are limited in resources compared to personal computers (PC), streaming sometimes is the only way to deliver media contents to user. This work targets devices in the so-called “ad-hoc situation”, and also seeks to save the cost associated with multimedia streaming, which traditionally uses the operator wireless network, by using a LAN-connected proxy and the Bluetooth medium. It is also to serve the educational purpose in learning about multimedia streaming on cellular phones. This project experiments with several approaches to implement streaming on mobile phones. It discusses each approach in details. Finally, a library and a sample application are implemented to demonstrate the solution

Cloudlet-based just-in-time indexing of IoT video

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Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years

Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

Publisher PD