Real-Time Systems and Programming Languages: ADA 95, Real-Time Java, and Real-Time POSIX
Real-Time Systems and Programming Languages: ADA 95, Real-Time Java, and Real-Time POSIX
The Aperiodic Multiprocessor Utilization Bound for Liquid Tasks
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
Analyzing Fixed-Priority Global Multiprocessor Scheduling
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
Global Priority-Driven Aperiodic Scheduling on Multiprocessors
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Partitioned Aperiodic Scheduling on Multiprocessors
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Schedulability Analysis and Utilization Bounds for Highly Scalable Real-Time Services
RTAS '01 Proceedings of the Seventh Real-Time Technology and Applications Symposium (RTAS '01)
Static-Priority Scheduling on Multiprocessors
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
AICCSA '08 Proceedings of the 2008 IEEE/ACS International Conference on Computer Systems and Applications
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We provide a constant time schedulability test and priority assignment algorithm for an on-line multiprocessor server handling aperiodic tasks. The so called Dhall's effect is avoided by dividing tasks in two priority classes based on their utilization: heavy and light. The improvement in this paper is due to assigning priority of light tasks based on slack--not on deadlines. We prove that if the load on the multiprocessor stays below $(3 - \sqrt{5} )/2 \approx 38.197\%$ , the server can accept an incoming aperiodic task and guarantee that the deadlines of all accepted tasks will be met. This is better than the current state-of-the-art algorithm where the priorities of light tasks are based on deadlines (the corresponding bound is in that case 35.425%).The bound $(3 - \sqrt{5} )/2$ can be improved if the number of processors m is known. There is a formula for the sharp bound $U_{\mathit{threshold}}(m) = \frac{3m - 2 - \sqrt{5m^{2} - 8m + 4}}{2(m - 1)}$ , which converges to $(3 - \sqrt{5} )/2$ from above as m驴驴. For m驴3, the bound is higher (i.e., better) than the corresponding sharp bound for the state-of-the-art algorithm where the priorities of light tasks are based on deadlines.A simulation study also indicates that when m3 the best effort behavior of the priority assignment scheme suggested here is better than that of the traditional scheme where priorities are based on deadlines.