This paper presents an Adaptive Policy Increment Processor(APIP) model and realization scheme, which can automatically accomplish policy increment distribution based on the change of the PEP's policy.
基于此,提出了一种自适应增量策略处理机(APIP)的数学模型和实现方案,根据PEP在策略库的策略映射集合的变化情况,自动实现策略的增量分发。
With adaptive spinning the duration of the spin is not fixed anymore, but determined by a policy based on previous spin attempts on the same lock and the state of the lock owner.
自适应意味着自旋的时间不再固定了,而是取决于一个基于前一次在同一个锁上的自旋时间以及锁的拥有者的状态。
Active label layering, adaptive utility layering policy, hop-by-hop feedback merging and active rate control algorithms are adopted in DL-AALM scheme.
该方案采用了主动标记分层、适应性效用分层策略、逐跳反馈归并以及主动速率控制算法。
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