Efficient Methods for Scheduling Jobs in a Simulation Model Using a Multicore Multicluster Architecture

Authors

  • Francisca A. P. Pinto Department of Computer Science, University of Rio Grande do Norte (UERN), Rural University of the Semi-Arid (UFERSA) & Secretariat of Education of the State of Ceará (SEDUC-CE), Fortaleza, CE, Brazil
  • Henrique J. A. Holanda Department of Computer Science, University of Rio Grande do Norte (UERN), 59610-210, Mossoró, RN, Brazil
  • Carla K. de M. Marques Department of Computer Science, University of Rio Grande do Norte (UERN), 59610-210, Mossoró, RN, Brazil
  • Giovanni C. Barroso Engineering Department of Teleinformatics, Federal University of Ceará (UFC), 60455-760, Fortaleza, CE, Brazil

DOI:

https://doi.org/10.31577/cai_2019_2_390

Keywords:

Multicluster, parallel jobs, migration, gang scheduling, distributed system

Abstract

Over the past decade, the fast advance of network technologies, hardware and middleware, as well as software resource sophistication has contributed to the emergence of new computational models. Consequently, there was a capacity increasing for efficient and effective use of resources distributed aiming to integrate them, in order to provide a widely distributed environment, which computational capacity could be used to solve complex computer problems. The two most challenging aspects of distributed systems are resource management and task scheduling. This work contributes to minimize such problems by i) aiming to reduce this problem through the use of migration techniques; ii) implementing a multicluster simulation environment with mechanisms for load balancing; iii) plus, the gang scheduling implementation algorithms will be analyzed through the use of metrics, in order to measure the schedulers performance in different situations. Thus, the results showed a better use of resources, implying operating costs reduction.

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Published

2019-05-31

How to Cite

Pinto, F. A. P., Holanda, H. J. A., Marques, C. K. de M., & Barroso, G. C. (2019). Efficient Methods for Scheduling Jobs in a Simulation Model Using a Multicore Multicluster Architecture. Computing and Informatics, 38(2), 390–420. https://doi.org/10.31577/cai_2019_2_390