新鲜度敏感的上下文推理实时调度算法

由于普适计算中上下文具有时效性，上下文推理器必须支持推理任务的实时调度。针对上下文推理结果在一段时间内仍然保持新鲜的特点，本文提出推理结果重复利用效率及其计算公式。在此基础上提出一种新鲜度敏感的上下文推理实时调度算法FRSA，以推理结果重复利用效率作为判断依据结合任务的deadline进行调度，其目标是在推理器负载较重时达到较高吞吐量。实验表明，在推理器负载重时，FRSA的系统吞吐量比经典调度算法(SJF，EDF，LSF和FCFS)高出10%-30%。

Freshness-Aware Real-Time Scheduling Algorithm for Context Reasoning

Due to the dynamic nature of contexts in pervasive computing, a context reasoner has to support real-time scheduling of reasoning jobs. Due to the fact that reasoning results remain fresh within a period of time, the concept of reasoning result reuse efficiency and its computation method are proposed. Then a Fresh-aware Real-time Scheduling Algorithm (FRSA) is proposed to promote the system throughput when the reasoner is overloaded, which schedules reasoning jobs according to their result reuse efficiencies and deadlines. The simulation demonstrates that when the reasoner is heavily overloaded, the throughput of FRSA is 10% to 30% better than those of classic scheduling algorithms SJF, EDF, LSF and FCFS.