A new two-stage soft real-time scheduling algorithm based on priority table was proposed for task dispatch and selection in cluster systems with inaccurate parameters. The inaccurate characteristics of the system were...A new two-stage soft real-time scheduling algorithm based on priority table was proposed for task dispatch and selection in cluster systems with inaccurate parameters. The inaccurate characteristics of the system were modeled through probability analysis. By taking into account the multiple important system parameters, including task deadline, priority, session integrity and memory access locality, the algorithm is expected to achieve high quality of service. Lots of simulation results collected under different load conditions demonstrate that the algorithm can not only effectively overcome the inaccuracy of the system state, but also optimize the task rejected ratio, value realized ratio, differentiated service guaranteed ratio, and session integrity ensured ratio with the average improvement of 3.5%, 5.8%, 7.6% and 5. 5%, respectively. Compared with many existing schemes that cannen deal with the inaccurate parameters of the system, the proposed scheme can achieve the best system performance by carefully adjusting scheduling probability. The algorithm is expected to be promising in systems with soft real-time scheduling requirement such as E-commerce applications.展开更多
基金Project(60573127) supported by the National Natural Science Foundation of China project(05JJ40131) supported by theNatural Science Foundation of Hunan Province
文摘A new two-stage soft real-time scheduling algorithm based on priority table was proposed for task dispatch and selection in cluster systems with inaccurate parameters. The inaccurate characteristics of the system were modeled through probability analysis. By taking into account the multiple important system parameters, including task deadline, priority, session integrity and memory access locality, the algorithm is expected to achieve high quality of service. Lots of simulation results collected under different load conditions demonstrate that the algorithm can not only effectively overcome the inaccuracy of the system state, but also optimize the task rejected ratio, value realized ratio, differentiated service guaranteed ratio, and session integrity ensured ratio with the average improvement of 3.5%, 5.8%, 7.6% and 5. 5%, respectively. Compared with many existing schemes that cannen deal with the inaccurate parameters of the system, the proposed scheme can achieve the best system performance by carefully adjusting scheduling probability. The algorithm is expected to be promising in systems with soft real-time scheduling requirement such as E-commerce applications.