Fixed Priority Scheduling Theory for Hard Real-Time Systems

Lehoczky, John P.; Sha, Lui; Strosnider, J.K.; Tokuda, Hide

doi:10.1007/978-1-4615-3956-8_1

Cited by 55 publications

(24 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Analytical methods for analyzing real-time systems also exist, such as the rate-monotonic scheduling theory [22,19,26]. In this method a real-time system is characterized by a set of periodic tasks, each having a period and an execution time.…”

Section: Related Methodsmentioning

confidence: 99%

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Campos

Grumberg

1996

Computer Aided Verification

View full text Add to dashboard Cite

In this work we propose a verification methodology consisting of selective quantitative analysis and interval model checking. Our methods can aid not only in determining if a system works correctly, but also in understanding how well the system works.The selective quantitative algorithms compute minimum and maximum delays over a selected subset of system executions. We use a formula of the linear-time temporal logic LTL in order to select either infinite paths or finite intervals over which the computation is performed. We therefore define two semantics for LTL -over infinite paths and over finite intervals. We show how tableaux for LTL formulas can be used for selecting either paths or intervals and can also be used for model checking formulas interpreted over paths or intervals.We have implemented a tool based on our techniques. To demonstrate the usefulness of our methods we verified a complex distributed real-time system. Several features of this example make it an interesting target for our techniques. It is a system of realistic complexity, its components are existing systems and protocols executing a mixture of multimedia, traditional real-time and non-real time tasks. Also, the distributed nature of the system makes the interaction among its various components much richer. This also makes its analysis more difficult.Out tool were able to analyze the system and verify that the deadlines are met by the design. Moreover, we have been able to identify inefficiencies that caused the response time to increase significantly (about 50%). After changing the design we not only verified that the response time was lower, but were also able to determine the causes for the poor performance of the original model using interval model checking.

show abstract

Section: Related Methodsmentioning

confidence: 99%

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Campos

Grumberg

1996

Computer Aided Verification

View full text Add to dashboard Cite

show abstract

“…A collection of results has been developed that is proving to be very useful and is gaining popularity as a basis for reasoning about the timing behavior of real-time systems. These results are summarized by Sha, Klein, and Goodenough [15], Sha and Goodenough [12] and Lehoczky, et al [6]. Aperiodic task scheduling has been treated in [16], synchronization requirements treated in [9,10,14], and mode change requirements treated in [11].…”

Section: Introductionmentioning

confidence: 99%

Timing analysis for fixed-priority scheduling of hard real-time systems

Harbour

Klein

Lehoczky

1994

IIEEE Trans. Software Eng.

129

View full text Add to dashboard Cite

show abstract

“…This generates a feasible schedule where all precedence constraints and all deadlines are met. Given the parameters of J , we can compute the set {uj} and use the existing schedulability bounds given in [11,12,13] to determine whether there is a set of {δj} where δi > 0 and m j=1 δj ≤ 1. The job system J can be feasibly scheduled in the manner described above if such a set of δj' exists.…”

Section: Periodic Flow Shopsmentioning

confidence: 99%

“…The total utilization factors on P1 and P2 for the job set in Table 4 are u1 = 0.4125 and u2 = 0.45, respectively. Equation (1) [12] gives the least upper bound of the total utilization; a set of jobs whose total utilization is equal to or less than umax(δ) is surely schedulable by the rate-monotone algorithm to complete within δpi units after their ready time.…”

Section: Periodic Flow Shopsmentioning

confidence: 99%

See 1 more Smart Citation

End-to-end scheduling to meet deadlines in distributed systems

Bettati

Liu

[1992] Proceedings of the 12th International Conference on Distributed Computing Systems

View full text Add to dashboard Cite

In a distributed system or communication network tasks may need to be executed on more than one processor. For time-critical tasks, the timing constraints are typically given as end-to-end release-times and deadlines. This paper describes algorithms to schedule a class of systems where all the tasks execute on different processors in turn in the same order. This end-to-end scheduling problem is known as the flow-shop problem. We present two cases where the problem is tractable and evaluate a heuristic for the N P-hard general case. We generalize the traditional flow-shop model in two directions. First, we present an algorithm for scheduling flow shops where tasks can be serviced more than once by some processors. Second, we describe a heuristic algorithm to schedule flow shops that consist of periodic tasks. Some considerations are made about scheduling systems with more than one flow shop.

show abstract

Fixed Priority Scheduling Theory for Hard Real-Time Systems

Cited by 55 publications

References 7 publications

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Timing analysis for fixed-priority scheduling of hard real-time systems

End-to-end scheduling to meet deadlines in distributed systems

Contact Info

Product

Resources

About