TY - JOUR
T1 - An intelligent data uploading selection mechanism for offloading uplink traffic of cellular networks
AU - Wang, Qian
AU - Fang, Juan
AU - Gong, Bei
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - Wi-Fi uploading is considered an effective method for offloading the traffic of cellular networks generated by the data uploading process of mobile crowd sensing applications. However, previously proposed Wi-Fi uploading schemes mainly focus on optimizing one performance objective: the offloaded cellular traffic or the reduced uploading cost. In this paper, we propose an Intelligent Data Uploading Selection Mechanism (IDUSM) to realize a trade-off between the offloaded traffic of cellular networks and participants’ uploading cost considering the differences among participants’ data plans and direct and indirect opportunistic transmissions. The mechanism first helps the source participant choose an appropriate data uploading manner based on the proposed probability prediction model, and then optimizes its performance objective for the chosen data uploading manner. In IDUSM, our proposed probability prediction model precisely predicts a participant’s mobility from spatial and temporal aspects, and we decrease data redundancy produced in the Wi-Fi offloading process to reduce waste of participants’ limited resources (e.g., storage, battery). Simulation results show that the offloading efficiency of our proposed IDUSM is (56.54 × 10−7), and the value is the highest among the other three Wi-Fi offloading mechanisms. Meanwhile, the offloading ratio and uploading cost of IDUSM are respectively 52.1% and (6.79 × 103). Compared with other three Wi-Fi offloading mechanisms, it realized a trade-off between the offloading ratio and the uploading cost.
AB - Wi-Fi uploading is considered an effective method for offloading the traffic of cellular networks generated by the data uploading process of mobile crowd sensing applications. However, previously proposed Wi-Fi uploading schemes mainly focus on optimizing one performance objective: the offloaded cellular traffic or the reduced uploading cost. In this paper, we propose an Intelligent Data Uploading Selection Mechanism (IDUSM) to realize a trade-off between the offloaded traffic of cellular networks and participants’ uploading cost considering the differences among participants’ data plans and direct and indirect opportunistic transmissions. The mechanism first helps the source participant choose an appropriate data uploading manner based on the proposed probability prediction model, and then optimizes its performance objective for the chosen data uploading manner. In IDUSM, our proposed probability prediction model precisely predicts a participant’s mobility from spatial and temporal aspects, and we decrease data redundancy produced in the Wi-Fi offloading process to reduce waste of participants’ limited resources (e.g., storage, battery). Simulation results show that the offloading efficiency of our proposed IDUSM is (56.54 × 10−7), and the value is the highest among the other three Wi-Fi offloading mechanisms. Meanwhile, the offloading ratio and uploading cost of IDUSM are respectively 52.1% and (6.79 × 103). Compared with other three Wi-Fi offloading mechanisms, it realized a trade-off between the offloading ratio and the uploading cost.
KW - Mobile crowd sensing applications
KW - Mobility prediction
KW - Opportunistic communications
KW - Uplink traffic offloading
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U2 - 10.3390/s20216287
DO - 10.3390/s20216287
M3 - Article
C2 - 33158266
AN - SCOPUS:85095740276
SN - 1424-8220
VL - 20
SP - 1
EP - 20
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 21
M1 - 6287
ER -