Multiprocessor online scheduling of hard-real-time tasks

Dertouzos, Michael L.; Mok, Aloysius K.

doi:10.1109/32.58762

Cited by 362 publications

(183 citation statements)

References 6 publications

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“…partitioned and global scheduling [10,11]. In partitioned scheduling, each task is assigned to a specific processor and processors can only execute tasks that are assigned to them.…”

Section: Related Workmentioning

confidence: 99%

“…In general, there are two major approaches for scheduling real-time tasks in multiprocessor realtime systems: partitioned and global scheduling [10,11]. With the emergence of multicore processors, where the shared cache architecture can significantly alleviate the task migration overhead for global scheduling, there is a reviving interest in global scheduling and many interesting results have been reported in recent years.…”

Section: Introductionmentioning

confidence: 99%

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An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

Zhu

Mossé

et al. 2011

Journal of Parallel and Distributed Computing

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Although the scheduling problem for multiprocessor real-time systems has been studied for decades, it is still an evolving research field with many open problems. In this work, focusing on periodic real-time tasks, we propose a novel optimal scheduling algorithm, namely boundary fair (Bfair), which follows the same line of research as the well-known Pfair scheduling algorithms and can also achieve full system utilization. However, different from the Pfair algorithms that make scheduling decisions at every time unit to enforce proportional progress (i.e., fairness) for each task, Bfair makes scheduling decisions and enforces fairness to tasks only at tasks' period boundaries. The correctness of the Bfair algorithm to meet the deadlines of all tasks' instances * A preliminary version of this paper appeared in IEEE RTSS 2003. This work is supported in part by NSF award CNS-0720651. 1 is formally proved. The performance of Bfair is evaluated through extensive simulations. The results show that, compared to that of the Pfair algorithms, Bfair can significantly reduces the number of scheduling points (by upto 94%) and the time overhead of Bfair is comparable to that of the most efficient Pfair algorithm (i.e., P D 2 ). Moreover, by aggregating the time allocation of tasks for the time interval between consecutive period boundaries, the resulting Bfair schedule needs dramatically reduced number of context switches and task migrations, as low as 18% and 15%, respectively, when compared to those of Pfair schedules.

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“…partitioned and global scheduling [10,11]. In partitioned scheduling, each task is assigned to a specific processor and processors can only execute tasks that are assigned to them.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

Zhu

Mossé

et al. 2011

Journal of Parallel and Distributed Computing

View full text Add to dashboard Cite

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“…The time complexity of Longest Successors' Execution Time First Algorithm is O(n 2 ). The algorithm is similar to the Least Slack Time First algorithm [13]. The difference is that each bus transaction does not have equal release time but has common deadline.…”

Section: Fig 6 the Initial Architecturementioning

confidence: 99%

On-Chip Bus Architecture Optimization for Multi-core SoC Systems

Lien

Chen

Shih

2007

Software Technologies for Embedded and Ubiquitous Systems

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Abstract. With the significant driving force from the application domains, modern embedded systems are designed over heterogeneous multicore SoC platforms. When more and more functions are integrated into one system, the designs of embedded systems have become more and more complicated. In particular, most of embedded multimedia applications are data intensive. Performance bottleneck are often caused by inappropriate bus architecture design within the system. In this paper, we present the algorithms for bus architecture optimization in MFASE. The algorithm takes the workloads in the system and their timing behavior requirements into account. The goal is to minimize the number of buses in the system without violating timing requirements. We prove that the minimzation problem is NP-hard and develop a heuristic algorithm. We evaluate the algorithm with extensive simulations. The performance results show that the algorithm reduce up to 80% of the bus cost and performs as well as optimal exponential algorithm does.

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“…Several algorithms are known to be optimal on a single machine [3]. But on multiple machines, the online problem is much more difficult than its offline counterpart.…”

Section: Introductionmentioning

confidence: 99%

“…But on multiple machines, the online problem is much more difficult than its offline counterpart. In fact, for m ≥ 2, there does not exist any optimal online algorithm [3]. To overcome this hardness, Phillips, Stein, Torng, and Wein [8] proposed the use of resource augmentation [5]: Given an online algorithm A we determine the speed s ≥ 1 such that A is optimal on m speed-s processors for any instance that is feasible for m processors of unit speed.…”

Section: Introductionmentioning

confidence: 99%

Meeting Deadlines: How Much Speed Suffices?

Anand

Gang

Megow

2011

Automata, Languages and Programming

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Abstract. We consider the online problem of scheduling real-time jobs with hard deadlines on m parallel machines. Each job has a processing time and a deadline, and the objective is to schedule jobs so that they complete before their deadline. It is known that even when the instance is feasible it may not be possible to meet all deadlines when jobs arrive online over time. We therefore consider the setting when the algorithm has available machines with speed s > 1. We present a new online algorithm that finds a feasible schedule on machines of speed e/(e − 1) ≈ 1.58 for any instance that is feasible on unit speed machines. This improves on the previously best known result which requires a speed of 2 − 2/(m + 1). Our algorithm only uses the relative order of job deadlines and is oblivious of the actual deadline values. It was shown earlier that the minimum speed required for such algorithms is e/(e − 1), and thus, our analysis is tight. We also show that our new algorithm outperforms two other well-known algorithms by giving the first lower bounds on their minimum speed requirement.

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Multiprocessor online scheduling of hard-real-time tasks

Cited by 362 publications

References 6 publications

An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

On-Chip Bus Architecture Optimization for Multi-core SoC Systems

Meeting Deadlines: How Much Speed Suffices?

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