Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In hard real-time systems, a computationally expensive schedulability analysis has to be performed for every task. Fulfilling this requirement is particularly tough when system workload and service capacity are not available a priori and thus the analysis has to be conducted at runtime.  presents an approach for applying control-theory-based admission control to predict the task schedulability so that the exact schedulability analysis is performed only to the tasks with positive prediction results. In case of a careful fine-tuning of parameters, the proposed approach can be successfully applied even to many-core embedded systems with hard real-time constraints and other time-critical systems. The provided experimental results demonstrate that, on average, only 62i¾ź% of the schedulability tests have to be performed in comparison with the traditional, open-loop approach. The proposed approach is particularly beneficial for heavier workloads, where the number of executed tasks is almost unchanged in comparison with the traditional open-loop approach. By our approach, only 32i¾ź% of exact schedulability tests have to be conducted. Moreover, for the analysed industrial workloads with dependent jobs, the proposed technique admitted and executed 11i¾ź% more tasks while not violating any timing constraints.
['Piotr Dziurzanski', 'Amit Kumar Singh', 'Leandro Soares Indrusiak']
I am writing a research paper on a idea Feedback-Based Admission Control for Hard Real-Time Task Allocation Under Dynamic Workload on Many-Core Systems
[{"from": "human", "value": "I am writing a research paper on a idea Feedback-Based Admission Control for Hard Real-Time Task Allocation Under Dynamic Workload on Many-Core Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In hard real-time systems, a computationally expensive schedulability analysis has to be performed for every task. Fulfilling this requirement is particularly tough when system workload and service capacity are not available a priori and thus the analysis has to be conducted at runtime.  presents an approach for applying control-theory-based admission control to predict the task schedulability so that the exact schedulability analysis is performed only to the tasks with positive prediction results. In case of a careful fine-tuning of parameters, the proposed approach can be successfully applied even to many-core embedded systems with hard real-time constraints and other time-critical systems. The provided experimental results demonstrate that, on average, only 62i\u00be\u017a% of the schedulability tests have to be performed in comparison with the traditional, open-loop approach. The proposed approach is particularly beneficial for heavier workloads, where the number of executed tasks is almost unchanged in comparison with the traditional open-loop approach. By our approach, only 32i\u00be\u017a% of exact schedulability tests have to be conducted. Moreover, for the analysed industrial workloads with dependent jobs, the proposed technique admitted and executed 11i\u00be\u017a% more tasks while not violating any timing constraints."}]