Encryption Mechanism And Resource Allocation Optimization Based On Edge Computing Environment

TL;DR

This paper presents an edge computing-based encryption and resource allocation method that balances privacy protection with task offloading efficiency, optimizing latency and preserving user data accuracy.

Contribution

It introduces a joint optimization algorithm for task offloading and resource allocation that considers privacy, latency, and contextual data interference in edge environments.

Findings

Effective privacy-preserving task offloading in edge computing

Reduced latency through joint optimization

Balanced privacy and accuracy in task distribution

Abstract

A method for optimizing encryption mechanism and resource allocation based on edge computing environment is proposed. A local differential privacy algorithm based on a histogram algorithm is used to protect user information during task offloading, which allows accurate preservation of user contextual information while reducing interference with the playback decision. To efficiently offload tasks and improve offloading performance, a joint optimization algorithm for task offloading and resource allocation is proposed that optimizes overall latency. A balance will be found between privacy protection and task offloading accuracy. The impact of contextual data interference on task offloading decisions is minimized while ensuring a predefined level of privacy protection. In the concrete connected vehicle example, the method distributes tasks among roadside devices and neighboring vehicles with sufficient computational resources.