Evaluation of task clustering algorithm by FFT for heterogeneous distributed system

Hashimoto, Shuya; Weyulu, Emilia Ndilokelwa; Hajikano, Kazuo; Kanemitsu, Hidehiro; Kim, Moo Wan

doi:10.23919/icact.2017.7890064

Cited by 1 publication

(1 citation statement)

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“…Experimental results in a real environment show that the proposed task scheduling outperforms the method in [12] in terms of the schedule length. This paper is an extension of work originally presented in the 19th International Conference on Advanced Communications Technology(ICACT2017) [15].…”

Section: Introductionmentioning

confidence: 99%

On the Performance of a Clustering-based Task Scheduling in a Heterogeneous System

Kanemitsu¹,

Hanada²,

Weyulu³

et al. 2017

Adv. sci. technol. eng. syst. j.

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Recent task scheduling algorithms for a generalized workflow job in heterogeneous system adopt list-based scheduling. In those algorithms, the response time cannot be effectively reduced if the given workflow job is data-intensive. If the workflow job is computationally intensive, an attempt is made to assign tasks to many processors, which can lead to resource starvation. To this end, a task scheduling algorithm that is based on clustering tasks, called CMWSL (Clustering for Minimizing the Worst Schedule Length) has been proposed. In CMWSL, the lower bound of the assignment unit size for each processor is derived in order to suppress the total number of executing processors for effective use of processors. After the lower bound is derived, the processor as a assignment target is determined and then the assignment unit as a task cluster is generated. As a final phase of CMWSL, task ordering is performed for every assigned task. In this paper, we compare several task ordering methods in CMWSL in a real environment to find the best task ordering policy.

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Section: Introductionmentioning

confidence: 99%