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On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

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Frontiers of Information Technology & Electronic Engineering 

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


Author(s):  Chao JING, Jianwu XU

Affiliation(s):  College of Computer Science and Engineering, Guilin University of Technology, Guilin 541004, China; more

Corresponding email(s):  jingchao@glut.edu.cn

Key Words:  Collaborative edge computing; Task offloading; Privacy protection; Markov decision process


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Chao JING, Jianwu XU. PPDO: a privacy preservation-aware delay optimization task-offloading algorithm for collaborative edge computing[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2300741

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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 designed a privacy preservation-aware delay optimization task-offloading algorithm (PPDO) in a CEC system. By considering location and usage-pattern privacy protection, we established 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 leveraged a Markov decision processing (MDP) policy-iteration-based algorithm to minimize delays without compromising privacy. To simultaneously accelerate the MDP operation, we developed an extension that improves the PPDO by optimizing the action set. Finally, a comprehensive simulation was conducted using the EUA dataset. The results demonstrated that PPDO achieves the optimal trade-off between privacy protection and delay with a minimal delay compared with that of existing algorithms. Moreover, we examined the advantages and disadvantages of improving PPDO.

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