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Time-Cost efficient scheduling algorithms for executing workflow in infrastructure as a service clouds

Ghafouri, R ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1007/s11277-018-5895-y
  3. Publisher: Springer New York LLC , 2018
  4. Abstract:
  5. Cloud Computing enables delivery of IT resources over the Internet and follows the pay-as-you-go billing model. The cloud infrastructures can be used as an appropriate environment for executing of workflow applications. To execute workflow applications in this environment, it is necessary to develop the workflow scheduling algorithms that consider different QoS parameters such as execution time and cost. Therefore, in this paper we focus on two criteria: total completion time (makespan) and execution cost of workflow, and propose two heuristic algorithms: MTDC (Minimum Time and Decreased Cost) which aims to create a schedule that minimizes the makespan and decreases execution cost, and CTDC (Constrained Time and Decreased Cost) which is based on the first algorithm (MTDC) and aims to create a schedule that decreases the execution cost while satisfying the deadline constraint of the workflow application. The proposed algorithms are evaluated by a simulation process using WorkflowSim. To evaluate the proposed algorithms, the results of MTDC are compared with the results of HEFT (Heterogeneous Earliest Finish Time), and the results of CTDC are compared with the results of heuristic based algorithms [such as IC-PCP (IaaS Cloud Partial Critical Paths), IC-PCPD2 (Deadline Distribution) and BDHEFT (Budget and Deadline HEFT)] and meta-heuristic based algorithms [such as PSO (Particle Swarm Optimization) and CGA2 (Coevolutionary Genetic Algorithm with Adaptive penalty function)]. The results show that the proposed algorithms perform better than the mentioned algorithms in most cases. © 2018, Springer Science+Business Media, LLC, part of Springer Nature
  6. Keywords:
  7. Cost ; Deadline ; IaaS cloud ; Scheduling ; Workflow ; Budget control ; Costs ; Genetic algorithms ; Heuristic algorithms ; Infrastructure as a service (IaaS) ; Integrated circuits ; Particle swarm optimization (PSO) ; Adaptive penalty functions ; Cloud infrastructures ; Coevolutionary Genetic Algorithm ; Iaas clouds ; Partial critical path ; PSO(particle swarm optimization) ; Scheduling algorithms
  8. Source: Wireless Personal Communications ; Volume 103, Issue 3 , 2018 , Pages 2035-2070 ; 09296212 (ISSN)
  9. URL: https://link.springer.com/article/10.1007%2Fs11277-018-5895-y