Original scientific paper

https://doi.org/10.31803/tg-20210204183323

Bio-Inspired Workflow Scheduling on HPC Platforms

Mandeep Kaur ; Dept. of Comp. Sc., Savitribai Phule Pune University, SPPU Campus, Ganeshkhind Road, Pune, Maharashtra 411007, India
Sanjay Kadam ; Centre for Development of Advanced Computing, SPPU Campus, Ganeshkhind Road, Pune, Maharashtra 411007, India

Abstract

Efficient scheduling of tasks in workflows of cloud or grid applications is a key to achieving better utilization of resources as well as timely completion of the user jobs. Many scientific applications comprise several tasks that are dependent in nature and are specified by workflow graphs. The aim of the cloud meta-scheduler is to schedule the user application tasks (and the applications) so as to optimize the resource utilization and to execute the user applications in minimum amount of time. During the past decade, there have been several attempts to use bio-inspired scheduling algorithms to obtain an optimal or near optimal schedule in order to minimize the overall schedule length and to optimize the use of resources. However, as the number of tasks increases, the solution space comprising different tasks-resource mapping sequences increases exponentially. Hence, there is a need to devise mechanisms to improvise the search strategies of the bio-inspired scheduling algorithms for better scheduling solutions in lesser number of iterations/time. The objective of the research work in this paper is to use bio-inspired bacteria foraging optimization algorithm (BFOA) along with other heuristics algorithms for better search of the scheduling solution space for multiple workflows. The idea is to first find a schedule by the heuristic algorithms such as MaxMin, MinMin, and Myopic, and use these as initial solutions (along with other randomly generated solutions) in the search space to get better solutions using BFOA. The performance of our approach with the existing approaches is compared for quality of the scheduling solutions. The results demonstrate that our hybrid approach (MinMin/Myopic with BFOA) outperforms other approaches.

Keywords

BFOA; bio-inspired; cloud computing; HPC; makespan; scheduling; workflow

Hrčak ID:

253023

URI

https://hrcak.srce.hr/253023

Publication date:

3.3.2021.

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