Many suspensions, many problems: a review of self-suspending tasks in real-time systems

In general computing systems, a job (process/task) may suspend itself whilst it is waiting for some activity to complete, e.g., an accelerator to return data. In real-time systems, such self-suspension can cause substantial performance/schedulability degradation. This observation, first made in 1988, has led to the investigation of the impact of self-suspension on timing predictability, and many relevant results have been published since. Unfortunately, as it has recently come to light, a number of the existing results are flawed. To provide a correct platform on which future research can be built, this paper reviews the state of the art in the design and analysis of scheduling algorithms and schedulability tests for self-suspending tasks in real-time systems. We provide (1) a systematic description of how self-suspending tasks can be handled in both soft and hard real-time systems; (2) an explanation of the existing misconceptions and their potential remedies; (3) an assessment of the influence of such flawed analyses on partitioned multiprocessor fixed-priority scheduling when tasks synchronize access to shared resources; and (4) a discussion of the computational complexity of analyses for different self-suspension task models

Contributions à des problèmes d'ordonnancement en ligne (l'ordonnancement temps réel de tâches à suspension et l'ordonnancement par une machine à traitement par lot)

Durant cette thése, deux problèmes d ordonnancement en-ligne ont été étudiés. Le premier problème concerne l ordonnancement temps réel de tâches à suspension. Nous avons établi des résultats sur la difficulté à résoudre un tel problème d ordonnancement (complexité, anomalies d ordonnancement et non-optimalité des algorithmes en-ligne). Nous avons établi la non-compétitivité d algorithmes en-ligne pour deux critères de performances même quand ceux-ci disposent de plus de ressources que l adversaire. Enfin, nous avons étudié avec l analyse de compétitivité différents tests d ordonnançabilité. Le second problème se rapporte à l ordonnancement par une machine à traitement par lot. Plusieurs algorithmes en-ligne compétitifs ont été présentés pour des problèmes dont la taille des lots est non bornée dont aH qui fait partie des meilleurs algorithmes en-ligne pour le problème général (son ratio de compétitivité est égal à la borne inférieure du problème (1+p52)/2 ).POITIERS-BU Sciences (861942102) / SudocTOURS-Polytech'Informat.Product. (372612209) / SudocSudocFranceF

Stochastic Network Calculus for end-to-end delays distribution evaluation on an avionics switched Ethernet

International audienceAFDX (avionics full duplex switched Ethernet, AR-INC 664) used for modern aircraft such as Airbus A380 represents a major upgrade in both bandwidth and capability for aircraft data networks. Its reliance on Ethernet technology helps to lower some of the implementation costs, though the requirement for guaranteed service does present challenges to system designers. Thus, the problem is to prove that no frame will be lost by the network (no switch queue will overflow) and to evaluate the end-to-end transfer delay through the network. Several approaches have been proposed for this evaluation. Deterministic network calculus gives a guaranteed upper bound on end-to-end delays, while simulation produces more accurate results on a given set of scenarios. In this paper, we propose a stochastic network calculus approach in order to evaluate the distribution of end-to-end delays. We evaluate the pessimism of the results on some typical AFDX flows, as described by virtual links

On-line scheduling on a batch processing machine with unbounded batch size to minimize the makespan

International audienceWe present on-line algorithms to minimize the makespan on a single batch processing machine. We consider a parallel batching machine that can process up to b jobs simultaneously. Jobs in the same batch complete at the same time. Such a model of a batch processing machine has been motivated by burn-in ovens in final testing stage of semiconductor manufacturing. We deal with the on-line scheduling problem when jobs arrive over time. We consider a set of independent jobs. Their number is not known in advance. Each job is available at its release date and its processing requirement is not known in advance. This general problem with infinite machine capacity is noted 1∣p − batch, rj, b = ∞∣Cmax. Deterministic algorithms that do not insert idle-times in the schedule cannot be better than 2-competitive and a simple rule based on LPT achieved this bound [Z. Liu, W. Yu, Scheduling one batch processor subject to job release dates, Discrete Applied Mathematics 105 (2000) 129-136]. If we are allowed to postpone start of jobs, the performance guarantee can be improved to 1.618. We provide a simpler proof of this best known lower bound for bounded and unbounded batch sizes. We then present deterministic algorithms that are best possible for the problem with unbounded batch size (i.e., b = ∞) and agreeable processing times (i.e., there cannot exist an on-line algorithm with a better performance guarantee). We then propose another algorithm that leads to a best possible algorithm for the general problem with unbounded batch size. This algorithm improves the best known on-line algorithm (i.e. [G. Zhang, X. Cai, C.K. Wong, On-line algorithms for minimizing makespan on batch processing machines, Naval Research Logistics 48 (2001) 241-258]) in the sense that it produces a shortest makespan while ensuring the same worst-case performance guarantee

Negative results for scheduling independent hard real-time tasks with self-suspensions

International audienc

On-line minimization of makespan for single batching machine scheduling problems

International audienc

Ordonnancement temps réel avec profils variables de consommation d'énergie

International audienc

Probabilistic upper bounds for heterogeneous flows using a static priority queueing on an AFDX network

International audienceAFDX (avionics full duplex switched Ethernet, AR-INC 664) developed for the Airbus A380 represents a major upgrade in both bandwidth and capability. Its reliance on Ethernet technology helps to lower some implementation costs, but guaranteed service presents challenges for system designers. An analysis of end-to-end transfer delays through the network is required in order to determine upper bounds. The stochastic network calculus approach analytically determines worst-case probabilistic upper bounds in the context of homogeneous avionics flows without priorities. Such upper bounds can be exceeded with a given probability P UB , and are relevant in the context of avionics, where functions are designed to give accurate results even if they miss some frames. Nowadays, there is a need to handle new classes of traffics with different priorities (voice, video, best-effort, ...) on the same AFDX network with no consequences on existing avionic flows. This paper presents the application of the stochastic network calculus approach in the context of a static priority queueing service discipline and evaluates the influence of the service discipline on analytical probabilistic upper bounds

On-line scheduling on a single batching machine to minimize the makespan

International audienc