PPDO: a privacy-preservation-aware delay optimization task-offloading algorithm for collaborative edge computing

Abstract

Although collaborative edge computing (CEC) systems are beneficial in enhancing the performance of mobile edge computing (MEC), the issue of user privacy leakage becomes prominent during task offloading. To address this issue, we design a privacy-preservation-aware delay optimization task-offloading algorithm (PPDO) in a CEC system. By considering location and usage pattern privacy protection, we establish a privacy task model to interfere with the edge server and ensure user privacy. To address the extra delay arising from privacy protection, we subsequently leverage a Markov decision processing (MDP) policy-iteration-based algorithm to minimize delays without compromising privacy. To simultaneously accelerate the MDP operation, we develop an extension that improves the PPDO by optimizing the action set. Finally, a comprehensive simulation was conducted using the edge user allocation (EUA) dataset. The results demonstrated that PPDO achieves an optimal trade-off between privacy protection and delay with a minimum delay compared with existing algorithms. Moreover, we examined the advantages and disadvantages of improving PPDO.

Keywords

Collaborative edge computing / Task offloading / Privacy protection / Markov decision process

RIGHTS & PERMISSIONS

Zhejiang University Press