| Title | Scheduling Crowdsensing Data to Smart City Applications in the Cloud |
|---|---|
| ID_Doc | 45513 |
| Authors | Alkhelaiwi, A; Grigoras, D |
| Title | Scheduling Crowdsensing Data to Smart City Applications in the Cloud |
| Year | 2016 |
| Published | |
| Abstract | Mobile phones and their sensing capabilities might be the main source of data for smart city applications. However, before sending a large amount of data to the cloud, it is essential to make sure that the data collected are useful. In this paper, we present a cloud architecture for smart city applications that provides, as a main service, a scheduler for controlling the transmission of data to the cloud. This scheduler will run as close to the crowd data sources as possible (i.e., public local servers). Data with a high priority value are sent to the cloud first. We designed an application for the Android platform to carry out experiments with the scheduling process. The simulation results are included in this paper |
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