Workflow Scheduling Algorithms for Hard-deadline Constrained Cloud Environments | Zendy

Alexander Visheratin | Zendy; Mikhail Melnik | Zendy; Denis Nasonov | Zendy

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Workflow Scheduling Algorithms for Hard-deadline Constrained Cloud Environments

Author(s) -

Alexander Visheratin,

Mikhail Melnik,

Denis Nasonov

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.05.529

Subject(s) - computer science , distributed computing , cloud computing , scheduling (production processes) , initialization , job shop scheduling , workflow , fair share scheduling , quality of service , dynamic priority scheduling , earliest deadline first scheduling , algorithm , rate monotonic scheduling , mathematical optimization , computer network , operating system , schedule , database , mathematics , programming language

Cloud computational platforms today are very promising for execution of scientific applications since they provide ready to go infrastructure for almost any task. However, complex tasks, which contain a large number of interconnected applications, which are usually called workflows, require efficient tasks scheduling in order to satisfy user defined QoS, like cost or execution time (makespan). When QoS has some restrictions – limited cost or deadline – scheduling becomes even more complicated. In this paper we propose heuristic algorithm for scheduling workflows in hard-deadline constrained clouds – Levelwise Deadline Distributed Linewise Scheduling (LDD-LS) – which, in combination with implementation of IC-PCP algorithm, is used for initialization of proposed metaheuristic algorithm – Cloud Deadline Coevolutional Genetic Algorithm (CDCGA). Experiments show high efficiency of CDCGA, which makes it potentially applicable for scheduling in cloud environments

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