Privacy-Preserving Computation Offloading for Intelligent Connected Vehicles via a Joint-Objective Alternating Multiplier Method

Key Points

• The research aims to optimize computation offloading while ensuring data privacy in intelligent connected vehicles.
• Developed a joint-objective alternating multiplier method for computation offloading.
• Applied techniques to evaluate the effectiveness of privacy preservation during computation.
• Analyzed the performance implications of the proposed method on connected vehicles.
• Demonstrated improved privacy protection during offloading processes.
• Showed efficient computation performance without compromising data security.
• Indicated positive outcomes for intelligent connected vehicle applications.

Abstract