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.... example, some policy may attempt to minimize number of tasks which miss their deadlines, another could try to minimize lateness (time by which a deadline is missed, more precisely, completion time deadline) Among the policies that we have tried out is the earliest deadline rst policy (EDF) [5, 6], which has the desirable property of being optimal. A policy is said to be optimal if it is able to nd a schedule meeting all deadlines if one exists. Another policy called least laxity(deadline completion time) rst (LLF) 5, 6] provides a di erent type of guarantee it minimizes maximum ....

....we have tried out is the earliest deadline rst policy (EDF) 5, 6] which has the desirable property of being optimal. A policy is said to be optimal if it is able to nd a schedule meeting all deadlines if one exists. Another policy called least laxity(deadline completion time) rst (LLF) [5, 6], provides a di erent type of guarantee it minimizes maximum lateness. However it su ers from the drawback of requiring an estimate of completion time of all threads, and poor estimates may lead to skewed scheduling. Compared to LLF, EDF is preferred because it does not need completion time ....

Cliord W. Mercer. An Introduction to Real Time Operating Systems : Scheduling Theory.

.... For example, some policy may attempt to minimize number of tasks which miss their deadlines, another could try to minimize lateness (time by which a deadline is missed, more precisely, completion time deadline) Among the policies that we have tried out is the earliest deadline rst policy(EDF) [5, 6], which has the desirable property of being optimal. A policy is said to be optimal if it is able to nd a schedule meeting all deadlines if one exists. Another policy called least laxity(deadline completion time) rst (LLF) 5, 6] provides a di erent type of guarantee it minimizes maximum ....

....that we have tried out is the earliest deadline rst policy(EDF) 5, 6] which has the desirable property of being optimal. A policy is said to be optimal if it is able to nd a schedule meeting all deadlines if one exists. Another policy called least laxity(deadline completion time) rst (LLF) [5, 6], provides a di erent type of guarantee it minimizes maximum lateness. However it su ers from the drawback of requiring an estimate of completion time of all threads, and poor estimates may lead to skewed scheduling. Compared to LLF, EDF is preferred because it does not need completion time ....

Cliord W. Mercer. An Introduction to Real Time Operating Systems: Scheduling Theory. Technical Report. (http://www.cs.cmu.edu/afs/cs/project/rtmach/ public/papers/sur1.review.ps)

....in soft real time systems Because of their impact on performance, scheduling issues are very important in the design of all concurrent systems including soft real time systems. There is a large literature on scheduling: a good survey of scheduling in real time systems is given by Mercer [44]. Earliest Deadline First (EDF) is the scheduling policy used in the research described in this thesis. The following sections introduce and provide background on EDF. Static priority scheduling, a very simple policy, is described first. Then a benefit of allowing priorities to change, that is of ....

Cli#ord W. Mercer. An introduction to real-time operating systems: Scheduling theory. http://www.cs.cmu.edu/afs/cs/project/art-6/www/publications.html, November 1992.

....Though a task or a computation may complete at a much later time than desired, the computation is still of value. Value functions are used in some real time scheduling algorithms. However, computationally, scheduling that utilizes even the simplest forms of value functions becomes unmanageable [39]. Tokuda et al. [55] implemented some canonical value functions, and compared their run time costs in comparison to various classical real time scheduling algorithms. The results indicated a significant amount of scheduling overhead, and that in numerous instances, the cost of making a single ....

Clifford W. Mercer. An introduction to real-time operating systems: Scheduling theory. Dept. of Computer Science, Carnegie Mellon University, November 1992.

....Readings 1 Introduction [59] 2 Real Time Project Formulation: Software Life Cycle Models Lecture Notes 3 Real Time Requirements and Specification Methods [11, 29: Chapter 5] 4 Real Time Requirements and Specification Methods Continued Add. Ref. 2, 3, 13, 17, 32, 43, 65, 67] 5 Scheduling Issues [42, 61, 63] 6 Case Study: Chimera Add. Ref. 7, 14, 15, 33, 58, 62, 68] 7 Rate Monotonic Scheduling (RMS) and Rate Monotonic Analysis (RMA) 52, 53, 54] 8 RMA Continued Add. Ref. 36] 9 Language Issues [26, 29: Chapter 3] 10 C Tutorial 11 Ada Tutorial [5] 12 Ada Continued Add. Ref. 19, 31, 38] 13 Cyclic ....

Mercer, C. W. (1992). An Introduction to Real-Time Operating Systems: Scheduling Theory. Carnegie Mellon University, School of Computer Science Working Paper, Pittsburgh, Pa.

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