An efficient greedy task scheduling algorithm for heterogeneous inter-dependent tasks on computational grids
by D.B. Srinivas; Sujay N. Hegde; M.A. Rajan; H.K. Krishnappa
International Journal of Grid and Utility Computing (IJGUC), Vol. 11, No. 5, 2020

Abstract: Designing a task scheduling algorithm for precedence constrained task graphs is still a challenge due to its complexity (NP-complete). Hence the majority of the research in this area is devoted to designing optimal scheduler based on a plethora of techniques such as heuristic, greedy, genetic, game theory, bio-inspired, machine learning etc. for fully dependent or independent task graphs. Motivated by these works, we propose an efficient greedy task scheduling algorithm for precedence constrained task graphs with varied dependencies (no, partial and fully) on computational grids. Performance of the proposed task scheduling algorithm is compared with respect to Turn Around Time (TAT) and grid utilisation against Hungarian, Partial Precedence Constrained (P_PCS) and AND scheduling algorithms. Simulation results shows that the performance of the proposed scheduling algorithm is on a par with Hungarian, P_PCS and AND scheduling algorithms and the running time of proposed algorithm is better than Hungarian and is on a par with P_PCS algorithm.

Online publication date: Fri, 02-Oct-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Grid and Utility Computing (IJGUC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com