TY - GEN
T1 - Privacy-aware service migration for edge computing in urban cities
AU - Liu, Xihua
AU - Qi, Lianyong
AU - Xu, Xiaolong
AU - Zhang, Xuyun
AU - Wan, Shaohua
PY - 2019
Y1 - 2019
N2 - Currently, to satisfy the increasing demands for the computing and network resources at the edge of networks, edge computing has emerged as an efficient paradigm for real-time resource provisioning. Due to the unbalanced resource requests of mobile devices in the urban cities, the edge computing nodes (ECN) easily suffers from the underload or overload resource usage. Thus, it is of great importance to devise rational and effective service migration strategies to guarantee the overall performance of edge computing in the urban city. However, during the service migration between ECNs, the privacy information in the services is detected by the network, which may lead to the privacy leakage. To avoid privacy leakage and provide favorable computation performance including load balance as well as transmission time, it is necessary to seek appropriate service migration routes. In this paper, an optimization problem is formulated to minimize the transmission time and the load balance while protecting the privacy data during the service migration. Then, a privacy-aware service migration method, named PSM, is proposed in this paper. Finally, numerous experiments and evaluations are conducted to confirm the effectiveness and efficiency of our designed method.
AB - Currently, to satisfy the increasing demands for the computing and network resources at the edge of networks, edge computing has emerged as an efficient paradigm for real-time resource provisioning. Due to the unbalanced resource requests of mobile devices in the urban cities, the edge computing nodes (ECN) easily suffers from the underload or overload resource usage. Thus, it is of great importance to devise rational and effective service migration strategies to guarantee the overall performance of edge computing in the urban city. However, during the service migration between ECNs, the privacy information in the services is detected by the network, which may lead to the privacy leakage. To avoid privacy leakage and provide favorable computation performance including load balance as well as transmission time, it is necessary to seek appropriate service migration routes. In this paper, an optimization problem is formulated to minimize the transmission time and the load balance while protecting the privacy data during the service migration. Then, a privacy-aware service migration method, named PSM, is proposed in this paper. Finally, numerous experiments and evaluations are conducted to confirm the effectiveness and efficiency of our designed method.
KW - Edge computing
KW - Load balance
KW - Privacy leakage
KW - Service migration
KW - Transmission time
UR - http://www.scopus.com/inward/record.url?scp=85078571614&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-37337-5_34
DO - 10.1007/978-3-030-37337-5_34
M3 - Conference proceeding contribution
AN - SCOPUS:85078571614
SN - 9783030373368
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 425
EP - 436
BT - Cyberspace Safety and Security
A2 - Vaidya, Jaideep
A2 - Zhang, Xiao
A2 - Li, Jin
PB - Springer
CY - Switzerland
T2 - 11th International Symposium on Cyberspace Safety and Security, CSS 2019
Y2 - 1 December 2019 through 3 December 2019
ER -