计算机科学
计算卸载
云计算
移动云计算
移动边缘计算
移动计算
分布式计算
边缘计算
计算
计算机网络
GSM演进的增强数据速率
人工智能
操作系统
算法
作者
Jianhui Wang,Zhetao Li,Haolin Liu,Tie Qiu,Hongbin Luo
标识
DOI:10.1109/tmc.2025.3530480
摘要
Cloud service centers (CSCs) can purchase edge computation resources to improve service quality in mobile cloud-edge computing networks. However, edge servers (ESs) are owned by different entities, and dishonest entities may launch computational forgery attacks, i.e., the ES falsely reports its idle computation resources to win more tasks for increased revenue. Most existing approaches ignore the threat of dishonest ESs. To address the challenges, we design a Trust-based Computation Offloading (TCO) framework. First, we construct the problem for minimizing the difference between the CSC's cost and the expected revenue (DCER), which is a mixed-integer nonlinear programming problem. Second, we develop a trust-based computation offloading method that quickly finds a good solution by decomposing the problem. Finally, a two-tier trust evaluation method was proposed to obtain accurate trust values. Experimental results indicate that TCO's comprehensive performance surpasses the benchmarks and significantly enhances computation offloading reliability with a lower performance loss. Notably, tasks are preferentially offloaded to honest ESs to ensure their revenue and promote ESs’ honesty under the TCO framework. Additionally, compared with no trust mechanisms, TCO reduces the service timeout count in an interval by 34.37% - 73.80% with a performance loss of only 1.42% - 4.10%.
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