Lookup NU author(s): Sami Alajrami,
Professor Alexander Romanovsky
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by INSTICC, 2018.
For re-use rights please refer to the publisher's terms and conditions.
Using cloud computing to execute software processes brings several benefits to software development. Ina previous work, we proposed a reference architecture, which treats software processes as workflows anduses cloud computing to execute them. Scheduling the execution in the cloud impacts the execution cost andthe cloud resources utilization. Existing workflow scheduling algorithms target business and scientific (data-driven)workflows, but not software processes workflows. In this paper, we adapt three scheduling algorithmsfor our architecture and propose a fourth one; the Proportional Adaptive Task Schedule algorithm. We evaluatethe algorithms in terms of their execution cost, makespan and cloud resource utilization. Our results show thatour proposed algorithm saves between 19.74% and 45.78% of the execution cost and provides the best resource(virtual machine) utilization compared to the adapted algorithms while providing the second best makespan.
Author(s): Alajrami S, Romanovsky A, Gallina B
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 6th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2018
Year of Conference: 2018
Online publication date: 22/01/2018
Acceptance date: 01/12/2017
Date deposited: 26/12/2017