Decomposition Based Multi-objective Workflow Scheduling for Cloud Environments

EasyChair Preprint 2150

Abstract

Workflow is a group of tasks that are processed in a particular order to complete an application. Also, it is a popular paradigm used to model complex applications. Executing complex application in a distributed system such as cloud computing implicates optimization of several conflicting objectives such as monetary cost, energy consumption, total execution time of the application (makespan), etc. Regardless of this trend, most of the workflow scheduling approaches focused on single or bi-objectives optimization problem. In this paper, we considered the problem of workflow scheduling in a cloud environment as a multi-objective optimization problem, and hence proposed a multi-objective workflow-scheduling algorithm based on decomposition (WSABD). The proposed algorithm is capable of finding optimal solutions with a single run. Our evaluation results show that, by a single run, the proposed approach manages to obtain the Pareto Front solutions which are at least as good as schedules produced by running a single-objective scheduling algorithm with constraint for multiple times.

Keyphrases: CPU Frequency, Cloud Computing, Cloud Environment, Communication time, Pareto optimal, algorithm cloud computing, execution time, maximum cpu frequency, multi-objective, multi-objective optimization, objective optimization, objective optimization problem, objective optimization sub problem, objective workflow scheduling, optimization problem, pareto optimal objective vector, pricing model, reference point, scalar objective optimization sub, scalar optimization problem, scientific workflow, stopping criterion, weight vector, workflow scheduling

@booklet{EasyChair:2150,
  author    = {Emmanuel Bugingo and Wei Zheng and Dongzhan Zhang and Yingsheng Qin and Zhang Defu},
  title     = {Decomposition Based Multi-objective Workflow Scheduling for Cloud Environments},
  howpublished = {EasyChair Preprint 2150},
  year      = {EasyChair, 2019}}