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

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Abstract
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.
Keywords
WIRELESS DATA-NETWORKS, IBCN, ALGORITHMS, Content scheduling, large-scale user participation, video upstreaming, Wi-Fi DenseNets

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Citation

Please use this url to cite or link to this publication:

Chicago
Danneels, G, Jeroen Famaey, Steven Bohez, Pieter Simoens, and Steven Latré. 2015. “Upstream Content Scheduling in Wi-Fi DenseNets During Large-scale Events.” In 2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 1–7.
APA
Danneels, G., Famaey, J., Bohez, S., Simoens, P., & Latré, S. (2015). Upstream content scheduling in Wi-Fi DenseNets during large-scale events. 2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS) (pp. 1–7). Presented at the IEEE Globecom Workshops (GC Wkshps).
Vancouver
1.
Danneels G, Famaey J, Bohez S, Simoens P, Latré S. Upstream content scheduling in Wi-Fi DenseNets during large-scale events. 2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS). 2015. p. 1–7.
MLA
Danneels, G et al. “Upstream Content Scheduling in Wi-Fi DenseNets During Large-scale Events.” 2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS). 2015. 1–7. Print.
@inproceedings{7215320,
  abstract     = {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.},
  author       = {Danneels, G and Famaey, Jeroen and Bohez, Steven and Simoens, Pieter and Latré, Steven},
  booktitle    = {2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS)},
  isbn         = {978-1-4673-9526-7},
  keywords     = {WIRELESS DATA-NETWORKS,IBCN,ALGORITHMS,Content scheduling,large-scale user participation,video upstreaming,Wi-Fi DenseNets},
  language     = {eng},
  location     = {San Diego, USA},
  pages        = {1--7},
  title        = {Upstream content scheduling in Wi-Fi DenseNets during large-scale events},
  year         = {2015},
}

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