Trust-Aware Service Offloading for Video Surveillance in Edge Computing Enabled Internet of Vehicles

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.

Automated summary

The article introduces a trust-aware task offloading method for video surveillance in edge computing enabled IoV, aiming to reduce service response time, achieve load balance of edge nodes, and ensure privacy protection. By using the SPEA2 algorithm to obtain balanced task offloading solutions, followed by TOPSIS and MCDM methods to determine the optimal solution. Experimental simulation results demonstrate that this method is both efficient and trustworthy.