View source for Meta-scheduling

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'''Meta-scheduling''' or super scheduling is a [[computer software]] technique of optimizing computational workloads by combining an organization's multiple [[Job scheduler|job schedulers]] into a single aggregated view, allowing [[batch job]]s to be directed to the best location for execution.{{Clarify|date=February 2022|reason=Is this article about using specialized software to optimize job schedulers to *in turn* optimize the performance of parallel processing? If so, make this more explicit.}}

Meta-scheduling technique is a solution for scheduling a set of dependent or independent faults with different scenarios that are mapping and modeling in an event-tree. It can be used as a dynamic or static scheduling method.

== Scenario-based meta-scheduling ==
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Scenario-based and multi-mode approaches are essential techniques in embedded-systems, e.g., design space exploration for MPSoCs and reconfigurable systems.

Optimization techniques for the generation of schedule graphs supporting such a ''SBMeS'' approach have been developed and implemented. 

Scenario-based meta-scheduling can promise better performance by reducing dynamic [[scheduling analysis real-time systems|scheduling]] overhead and recovering from faults.

== Implementations ==
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The following is a partial list of noteworthy{{whom|date=September 2023}} open source and commercial meta-schedulers currently available.
* [[GridWay]] by the Globus Alliance
* Community Scheduler Framework by [[Platform Computing]] and [[Jilin University]]
* MP Synergy by [[United Devices]]
* Moab Cluster Suite and Maui Cluster scheduler from Adaptive Computing
* DIOGENES (distributed optimal genetic algorithm for grid applications scheduling, started project)
* [[SynfiniWay]]'s meta-scheduler
* MeS is designed to generate schedules for anticipated changes of scenarios by Dr.-Ing. Babak Sorkhpour and Prof. Dr.-Ing.Roman Obermaisser in chair for Embedded Systems in [[university of Siegen]] for [[Electrical efficiency|energy-efficient]], Robust and Adaptive [[Time-triggered architecture|Time-Triggered Systems]] (multi-core architectures with [[Network on a chip|Networks-on-chip]]).
* Accelerator Plus runs jobs by the use of host jobs in an underlying workload manager. This approach achieves high job throughput by distributing the processing load associated with submitting and managing jobs.

== References ==
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* {{cite web|url=http://www.mcs.anl.gov/~schopf/Pubs/sched.arch.2002.pdf|last=Schopf|first=Jennifer|title=A General Architecture for Scheduling on the Grid|publisher=Argonne National Laboratory|year=2002|url-status=dead|archiveurl=https://web.archive.org/web/20080924084325/http://www.mcs.anl.gov/~schopf/Pubs/sched.arch.2002.pdf|archivedate=2008-09-24}}

* B. Sorkhpour and R. Obermaisser. "[https://ieeexplore.ieee.org/abstract/document/8402816/ MeSViz: Visualizing Scenario-based Meta-Schedules for Adaptive Time-Triggered Systems.]". in ''AmE 2018-Automotive meets Electronics; 9th GMM-Symposium'', 2018, pp. 1–6
* B. Sorkhpour, R. Obermaisser and A. Murshed, "[https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8324961 Meta-Scheduling Techniques for Energy-Efficient, Robust and Adaptive Time-Triggered Systems]," in ''Knowledge-Based Engineering and Innovation (KBEI), 2017 IEEE 4th International Conference on'', Tehran, 2017.
*B. Sorkhpour, O. Roman, and Y. Bebawy, Eds., ''[https://ieeexplore.ieee.org/abstract/document/8727845/ Optimization of Frequency-Scaling in Time-Triggered Multi-Core Architectures using Scenario-Based Meta-Scheduling]'': “in ''AmE 2019-Automotive meets Electronics; 10th GMM-Symposium'' VDE, 2019
*B. Sorkhpour. "[https://dspace.ub.uni-siegen.de/handle/ubsi/1471 Scenario-based meta-scheduling for energy-efficient, robust and adaptive time-triggered multi-core architectures]", University of Siegen, Doctoral thesis, July 2019.

[[Category:Grid computing]]

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