ALEA 4: Job Scheduling Simulator
| Authors | |
|---|---|
| Year of publication | 2015 |
| MU Faculty or unit | |
| web | Software ALEA je k dispozici na webu: https://github.com/aleasimulator/alea |
| Description | ALEA is designed allows to study advanced scheduling techniques for planning various types of jobs in Grid-like environments. ALEA is able to deal with common problems of job scheduling in clusters and Grids, like heterogeneity of jobs and resources, dynamic runtime changes such as arrival of new jobs or machine failures adn provides a handful set of features including a large set of various scheduling algorithms, several standard workload parsers and a set of typical fairness-related job ordering policies. ALEA Simulator is based on the GridSim simulation toolkit which we extended to provide a simulation environment that supports simulation of varying job scheduling problems. To demonstrate the features of the Alea environment, we implemented an experimental centralised job scheduler which uses advanced scheduling techniques for schedule generation. By now local search-based optimization algorithms as well as classical queue-based policies such as FCFS, SJF or Easy Backfilling are supported. The scheduler is capable to handle dynamic situation when jobs appear in the system during simulation. In this case generated schedule is changing through time as some jobs are already finished while the new ones are arriving. Various workload traces are available either at http://www.fi.muni.cz/~xklusac/workload or at http://www.cs.huji.ac.il/labs/parallel/workload/logs.html. Sample data sets are provided within the distribution but only serve for demonstration purposes. With the lastest version 4, ALEA now represents a rather unique simulation tool with a large set of uncommon simulation capabilities that include, e.g., implementations of various scheduling algorithms, various fair-sharing policies, further enabling realistic system emulations including complex queue setups and various job-to-machine constraints, as well as supporting dynamic user-to-system interactions based on dynamic workload adaptation. |
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