Scipediacontent: Scipediacontent moved page Draft Content 550580367 to Pillmann et al 2018a

2021-02-02T01:42:18Z

Scipediacontent moved page Draft Content 550580367 to Pillmann et al 2018a

Scipediacontent: Created page with " == Abstract == While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly..."

2021-02-02T01:42:13Z

Created page with " == Abstract == While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly..."

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== Abstract ==

While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly up-to-date information for crowdsensing-enabled big data services in a smart city context. Consequently, upcoming 5G communication networks will be confronted with massive increases in Machine-type Communication (MTC) and require resource-efficient transmission methods in order to optimize the overall system performance and provide interference-free coexistence with human data traffic that is using the same public cellular network. In this paper, we bring together mobility prediction and machine learning based channel quality estimation in order to improve the resource-efficiency of car-to-cloud data transfer by scheduling the transmission time of the sensor data with respect to the anticipated behavior of the communication context. In a comprehensive field evaluation campaign, we evaluate the proposed context-predictive approach in a public cellular network scenario where it is able to increase the average data rate by up to 194% while simultaneously reducing the mean uplink power consumption by up to 54%.

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1805.06603 http://arxiv.org/abs/1805.06603]

* [http://arxiv.org/pdf/1805.06603 http://arxiv.org/pdf/1805.06603]

* [http://xplorestaging.ieee.org/ielx7/8672788/8690547/08690856.pdf?arnumber=8690856 http://xplorestaging.ieee.org/ielx7/8672788/8690547/08690856.pdf?arnumber=8690856],
: [http://dx.doi.org/10.1109/vtcfall.2018.8690856 http://dx.doi.org/10.1109/vtcfall.2018.8690856]

* [https://dblp.uni-trier.de/db/journals/corr/corr1805.html#abs-1805-06603 https://dblp.uni-trier.de/db/journals/corr/corr1805.html#abs-1805-06603],
: [https://arxiv.org/pdf/1805.06603.pdf https://arxiv.org/pdf/1805.06603.pdf],
: [https://ui.adsabs.harvard.edu/abs/2018arXiv180506603S/abstract https://ui.adsabs.harvard.edu/abs/2018arXiv180506603S/abstract],
: [https://arxiv.org/abs/1805.06603 https://arxiv.org/abs/1805.06603],
: [http://export.arxiv.org/pdf/1805.06603 http://export.arxiv.org/pdf/1805.06603],
: [https://jp.arxiv.org/abs/1805.06603?context=cs https://jp.arxiv.org/abs/1805.06603?context=cs],
: [https://export.arxiv.org/abs/1805.06603 https://export.arxiv.org/abs/1805.06603],
: [https://academic.microsoft.com/#/detail/2803710950 https://academic.microsoft.com/#/detail/2803710950]

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Scipediacontent: Scipediacontent moved page Draft Content 550580367 to Pillmann et al 2018a

Scipediacontent: Created page with " == Abstract == While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly..."