Data gathering and offloading in delay tolerant mobile networks.

Mobile sensing emerges as an important application for mobile networks. Smartphones equipped with sensors are used to monitor a diverse range of human activities. One key and challenging procedure of the mobile sensing applications is data gathering, where the sensed data from distributed mobile nodes are captured and uploaded to the cloud or base station for further processing. Yet the mobile sensing application, which usually periodically generates some sensed data, would definitely deteriorate the 3G quality because the network cannot cope with the high demand; and users would be charged at high prices by using the 3G channel, which makes the mobile sensing application infeasible. In this paper, we proposed a hybrid data gathering and offloading algorithm DGO for the mobile sensing applications. Besides the direct uploading through 3G or Wifi offloading, the sensed data could also be forwarded to other peer nodes through short range communications. Nodes collect meta-data such as remaining energy, contact regularity, and expected contact duration to calculate the upload/offload utility and upload priority for data segments. Based on these utility factors, each data segment could decide its own approach at a specific time for uploading. Experimental studies show that DGO is efficient in data gathering and data offloading in mobile sensing applications. Given the low accessibility of Wifi APs, DGO still gains about more than 30 % of data offloading compared with existing algorithms without much extra transmission overhead or delay. [ABSTRACT FROM AUTHOR]