Lin Xin, Li Shan-ping, Yang Zhao-hui. Freshness-Aware Real-Time Scheduling Algorithm for Context Reasoning[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1185-1188. doi: 10.3724/SP.J.1146.2008.00510
Citation:
Lin Xin, Li Shan-ping, Yang Zhao-hui. Freshness-Aware Real-Time Scheduling Algorithm for Context Reasoning[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1185-1188. doi: 10.3724/SP.J.1146.2008.00510
Lin Xin, Li Shan-ping, Yang Zhao-hui. Freshness-Aware Real-Time Scheduling Algorithm for Context Reasoning[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1185-1188. doi: 10.3724/SP.J.1146.2008.00510
Citation:
Lin Xin, Li Shan-ping, Yang Zhao-hui. Freshness-Aware Real-Time Scheduling Algorithm for Context Reasoning[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1185-1188. doi: 10.3724/SP.J.1146.2008.00510
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.
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