Paper Info
Title
Trust-Aware Service Offloading for Video Surveillance in Edge Computing Enabled Internet of Vehicles
Abstract
Internet of Vehicles (IoV) supports multiple traffic services by processing abundant data from sensors and video surveillance devices. With edge computing, video surveillance services can be certainly improved due to the handy resource provision for video storage and processing. Generally, to reduce the hardware and maintenance investment, it is a popular manner to deploy the limited amount of edge nodes along with the surveillance devices. However such edge node layout leads to the unstable service distribution and complicated data transmission across the surveillance devices and edge nodes, which consequently decreases the quality of the surveillance services. In addition, the service trustworthiness is suspected since the privacy information may be revealed to some extent during the data transmission. To combat these challenges, a trust-aware task offloading method (TOM) for video surveillance in edge computing enabled IoV is presented for minimizing the response time of the services, achieving the load balance of the edge nodes and realizing privacy protection. Technically, SPEA2 (improving the strength Pareto evolutionary algorithm) is employed to acquire balanced task offloading solutions. Then, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and MCDM (Multiple Criteria Decision Making) are exercised to ascertain the optimal solution. Finally, the experimental simulation demonstrates that TOM performs efficient and trust.
Year
DOI
Venue
2021
10.1109/TITS.2020.2995622
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
IoV,edge computing,privacy protection,task offloading,SPEA2
Journal
22
Issue
ISSN
Citations 
3
1524-9050
5
PageRank 
References 
Authors
0.39
0
6
Name
Order
Citations
PageRank
Xu Xiaolong142464.23
Qi Wu250.39
Lianyong Qi356057.12
Wanchun Dou487896.01
Sang-Bing Tsai586.53
Md. Zakirul Alam Bhuiyan656066.51