为了增强普适计算环境下实时应用的安全性,建立了安全关键的实时周期任务模型、任务安全开销模型和任务安全风险模型,提出一种安全风险感知的自适应调度算法.该算法依据实时周期任务可调度的本质特性,将调度问题转化为安全风险最小化的多阶段决策过程,并基于近似动态规划策略实现了安全性能确保和低复杂度的调度机制.实验结果表明,该算法可明显降低应用的安全风险,满足应用的安全需求,自适应普适计算的动态变化.
Security is of critical importance for real-time applications running on pervasive computing environments. Security-critical task model, security overhead model and security risk model are built for real-time periodic tasks, and a security risk-aware adaptive scheduling algorithm is proposed. According to inherent properties of real-time periodic tasks, the scheduling problem is transformed to a multi-stage decision-making procedure with the purpose of minimizing security risk. Based on approximate dynamic programming policy, the proposed algorithm is designed with security performance guaranteed and low-complexity mechanisms. Experimental results show that the proposed algorithm can significantly reduce security risk of applications, satisfy the security requirements, and adapt itself to dynamic pervasive computing environments.