TY - GEN
T1 - Privacy-Aware data offloading for mobile devices in edge computing
AU - Xu, Xiaolong
AU - Tang, Bowei
AU - Jiang, Gaoxing
AU - Liu, Xihua
AU - Xue, Yuan
AU - Yuan, Yuan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - To fulfill peoples requirements for low latency and strong computing power in mobile devices, edge computing emerges as a paradigm for realizing service provisioning in the edge of mobile cloud near the activity area of the mobile subscribers. Despite numerous advantages of edge computing, there is still a risk of leaking private user data, including identity information, address, etc., during the process of data offloading from mobile devices to edge nodes, which threatens personal and property security potentially. Therefore, it is of great importance of prohibiting privacy leakage for data offloading in edge computing. In repose to this requirement, a privacy-Aware data offloading method (PDO) in edge computing is proposed in this paper. Technically, the privacy of the data offloading in edge computing is analyzed in a formalized way. Then, an improved of strength pareto evolutionary algorithm (SPEA2) is employed to realize joint optimization of the average time of transmission and the privacy entropy. Finally, experimental evaluations are conducted to verify reliability and efficiency of PDO.
AB - To fulfill peoples requirements for low latency and strong computing power in mobile devices, edge computing emerges as a paradigm for realizing service provisioning in the edge of mobile cloud near the activity area of the mobile subscribers. Despite numerous advantages of edge computing, there is still a risk of leaking private user data, including identity information, address, etc., during the process of data offloading from mobile devices to edge nodes, which threatens personal and property security potentially. Therefore, it is of great importance of prohibiting privacy leakage for data offloading in edge computing. In repose to this requirement, a privacy-Aware data offloading method (PDO) in edge computing is proposed in this paper. Technically, the privacy of the data offloading in edge computing is analyzed in a formalized way. Then, an improved of strength pareto evolutionary algorithm (SPEA2) is employed to realize joint optimization of the average time of transmission and the privacy entropy. Finally, experimental evaluations are conducted to verify reliability and efficiency of PDO.
KW - data offloading
KW - edge computing
KW - privacy entropy
KW - privacy preservation
KW - transmission time
UR - http://www.scopus.com/inward/record.url?scp=85074861505&partnerID=8YFLogxK
U2 - 10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00049
DO - 10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00049
M3 - 会议稿件
AN - SCOPUS:85074861505
T3 - Proceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
SP - 170
EP - 175
BT - Proceedings - 2019 IEEE International Congress on Cybermatics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
Y2 - 14 July 2019 through 17 July 2019
ER -