{"title":"多处理器双临界系统中低临界任务的优雅退化","authors":"Lin Huang, I.-Hong Hou, S. Sapatnekar, Jiang Hu","doi":"10.1145/3273905.3273909","DOIUrl":null,"url":null,"abstract":"According to the conventional mixed-criticality (MC) system model, low-criticality tasks are completely discarded in high-criticality system mode. Allowing such loss of low-criticality tasks is controversial and not obviously necessary. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and fpEDF-VD scheduling. It is found that the two scheduling methods in VMPC retain the same speedup factors as in conventional MC systems. We develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux prototyping with consideration of overhead. The results show that schedulability degradation caused by continuing low-criticality task execution is often very small. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode. The prototyping results indicate that partitioned scheduling in VPMC outperforms the latest work based on fluid model.","PeriodicalId":236964,"journal":{"name":"Proceedings of the 26th International Conference on Real-Time Networks and Systems","volume":"902 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Graceful Degradation of Low-Criticality Tasks in Multiprocessor Dual-Criticality Systems\",\"authors\":\"Lin Huang, I.-Hong Hou, S. Sapatnekar, Jiang Hu\",\"doi\":\"10.1145/3273905.3273909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the conventional mixed-criticality (MC) system model, low-criticality tasks are completely discarded in high-criticality system mode. Allowing such loss of low-criticality tasks is controversial and not obviously necessary. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and fpEDF-VD scheduling. It is found that the two scheduling methods in VMPC retain the same speedup factors as in conventional MC systems. We develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux prototyping with consideration of overhead. The results show that schedulability degradation caused by continuing low-criticality task execution is often very small. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode. The prototyping results indicate that partitioned scheduling in VPMC outperforms the latest work based on fluid model.\",\"PeriodicalId\":236964,\"journal\":{\"name\":\"Proceedings of the 26th International Conference on Real-Time Networks and Systems\",\"volume\":\"902 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 26th International Conference on Real-Time Networks and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3273905.3273909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 26th International Conference on Real-Time Networks and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3273905.3273909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Graceful Degradation of Low-Criticality Tasks in Multiprocessor Dual-Criticality Systems
According to the conventional mixed-criticality (MC) system model, low-criticality tasks are completely discarded in high-criticality system mode. Allowing such loss of low-criticality tasks is controversial and not obviously necessary. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and fpEDF-VD scheduling. It is found that the two scheduling methods in VMPC retain the same speedup factors as in conventional MC systems. We develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux prototyping with consideration of overhead. The results show that schedulability degradation caused by continuing low-criticality task execution is often very small. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode. The prototyping results indicate that partitioned scheduling in VPMC outperforms the latest work based on fluid model.