The Community for Technology Leaders
RSS Icon
Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
ISBN: 978-1-4673-2892-0
pp: 638-645
Although there are few efficient algorithms in the literature for scientific workflow tasks allocation and scheduling for heterogeneous resources such as those proposed in grid computing context, they usually require a bounded number of computer resources that cannot be applied in Cloud computing environment. Indeed, unlike grid, elastic computing, such asAmazon's EC2, allows users to allocate and release compute resources on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of resources is infinite. This feature of Clouds has been called âillusion of infiniteresourcesâ. However, despite the proven benefits of using Cloud to run scientific workflows, users lack guidance for choosing between multiple offering while taking into account several objectives which are often conflicting. On the other side, the workflow tasks allocation and scheduling have been shown to be NP-complete problems. Thus, it is convenient to use heuristic rather than deterministic algorithm. The objective of this paper is to design an allocation strategy for Cloud computing platform. More precisely, we propose three complementary bi-criteria approaches for scheduling workflows on distributed Cloud resources, taking into account the overall execution time and the cost incurred by using a set of resources.
Resource management, Virtual machining, Processor scheduling, Cloud computing, Scheduling, Schedules, Computational modeling
Kahina Bessai, Samir Youcef, Ammar Oulamara, Claude Godart, Selmin Nurcan, "Bi-criteria Workflow Tasks Allocation and Scheduling in Cloud Computing Environments", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 638-645, doi:10.1109/CLOUD.2012.83
52 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool