Upstream content scheduling in Wi-Fi DenseNets during large-scale events

The smartphone revolution and widespread availability of wireless LAN and mobile Internet technologies has changed the way people interact with the world. These technologies can be exploited by event organisers to boost audience involvement and immersion, for example, by integrating user-generated content into the event experience. In this paper, we developed a large-scale event participation platform for the wireless transmission of user-generated videos to be used during the event. Such events often bring together thousands of users on a small geographical area and providing wireless connectivity in such dense environments is highly challenging. We analysed the efficiency of several upload scheduling strategies in WiFi DenseNets based on extensive experiments performed in a shielded lab environment. We showed that intelligent scheduling improved throughput over 20% compared to uncoordinated uploading in a dense network, with more expected gains when the density would further increase. Moreover, we also calculated the theoretical scalability of the platform. Based on our results, we confirm the importance of content scheduling to efficiently utilise WLAN technologies in highly dense environments

The crowd as a cameraman : on-stage display of crowdsourced mobile video at large-scale events

Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. These videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes

Non-Real-Time Content Scheduling Algorithms For Wireless Data Networks

A substantial portion of the emerging wireless data service consists of non-real-time applications such as content download. The existing mechanisms based on per-packet performance guarantees used mainly for voice and streaming media do not suffice for the elastic nature of non-real-time traffic. For a non-real-time user data services, the key performance measure of interest is the total download time. In this paper, we propose a novel scheduling framework for wireless content service. Specifically, we present a two-layer scheduling architecture that combines content-aware scheduling with opportunistic scheduling. In terms of content-awareness, the proposed scheduling policy provides guarantees on the download time of content. In the second stage, the instantaneous channel conditions of different users are exploited in an opportunistic manner so as to maximize the throughput of the system. We define service differentiation in two modes - differential and guaranteed - and provide polynomial time algorithms for both that manipulate the stretch ratio but within allowable limits. Extensive simulations are conducted that verify the efficiency of the proposed schemes and provide insights into the behavior of the scheduling algorithms for non-real-time data. © 2006 IEEE

Non-real-time content scheduling algorithms for wireless data networks

A substantial portion of the emerging wireless data service consists of non-real-time applications such as content download. The existing mechanisms based on per-packet performance guarantees used mainly for voice and streaming media do not suffice for the elastic nature of non-real- time traffic. For a non-real- time user data services, the key performance measure of interest is the total download time. In this paper, we propose a novel scheduling framework for wireless content service. Specifically, we present a two-layer scheduling architecture that combines content-aware scheduling with opportunistic scheduling. In terms of content-awareness, the proposed scheduling policy provides guarantees on the download time of content. In the second stage, the instantaneous channel conditions of different users are exploited in an opportunistic manner so as to maximize the throughput of the system. We define service differentiation in two modes - differential and guaranteed - and provide polynomial time algorithms for both that manipulate the stretch ratio but within allowable limits. Extensive simulations are conducted that verify the efficiency of the proposed schemes and provide insights into the behavior of the scheduling algorithms for non-real- time data