TY - GEN
T1 - Trustworthy caching for mobile big data in social networks
AU - Xu, Qichao
AU - Su, Zhou
AU - Dai, Minghui
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/6
Y1 - 2018/7/6
N2 - Edge computing enabled social networks can improve the quality of experience (QoE) to deliver mobile big data to users, where multiple caches are placed at the edge of networks to help mobile users exchange and share contents. However, with the ever-increasing scale of mobile big data, how to provide a trustworthy caching scheme to deliver mobile social big data becomes a new challenge. To tackle the above problems, this paper presents a trustworthy edge caching scheme for mobile big data in social networks based on a matching game approach. Firstly, to guarantee the security of the networks, a trust evaluation mechanism is designed to evaluate the reliability of each edge node. Then, each content generator selects the optimal edge node to cache the content and determines the optimal caching size, where the interactions between edge nodes and mobile users are modeled by a matching game. Finally, the simulation results show that the proposal can not only improve the QoE of mobile users, but also can prevent the attacks of malicious edge nodes.
AB - Edge computing enabled social networks can improve the quality of experience (QoE) to deliver mobile big data to users, where multiple caches are placed at the edge of networks to help mobile users exchange and share contents. However, with the ever-increasing scale of mobile big data, how to provide a trustworthy caching scheme to deliver mobile social big data becomes a new challenge. To tackle the above problems, this paper presents a trustworthy edge caching scheme for mobile big data in social networks based on a matching game approach. Firstly, to guarantee the security of the networks, a trust evaluation mechanism is designed to evaluate the reliability of each edge node. Then, each content generator selects the optimal edge node to cache the content and determines the optimal caching size, where the interactions between edge nodes and mobile users are modeled by a matching game. Finally, the simulation results show that the proposal can not only improve the QoE of mobile users, but also can prevent the attacks of malicious edge nodes.
KW - Mobile social networks
KW - edge computing
KW - mobile big data
KW - multiple concurrent contents
KW - security
KW - trust evaluation
UR - https://www.scopus.com/pages/publications/85050661303
U2 - 10.1109/INFCOMW.2018.8406877
DO - 10.1109/INFCOMW.2018.8406877
M3 - 会议稿件
AN - SCOPUS:85050661303
T3 - INFOCOM 2018 - IEEE Conference on Computer Communications Workshops
SP - 808
EP - 812
BT - INFOCOM 2018 - IEEE Conference on Computer Communications Workshops
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018
Y2 - 15 April 2018 through 19 April 2018
ER -