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A Review on Energy-Aware Scheduling Techniques for Workflows in IaaS Clouds

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Abstract

Cloud computing has emerged as the preeminent computing platform for multiple enterprises. All scales of organizations adopt cloud services to leverage cloud technology to drive their businesses ahead. It is prevalent to use the workflow paradigm in modeling a wide variety of problems to compute in distributed environments. Cloud computing is mostly adapting technology to deal with workflow applications, particularly applications with unpredictable workloads. Due to the increased demand for cloud services, excessive power utilization in cloud data centers is a serious issue that needs to be addressed. Scientific workflow applications, in particular, consume high amounts of electrical energy. Many studies have been conducted on the consumption of energy in the cloud environment, and this area of research attracts people from all fields, including both research and business. For this paper, a survey was conducted on existing energy-efficient techniques for scheduling various workflows in a cloud environment. We targeted the methods that minimize energy consumption with assured quality of service constraints. This study on energy-aware and proper workflow scheduling provide extensive knowledge about various energy-aware scheduling paradigms currently going on. The review will help in listing the future directions in this field along with other factors included.

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The data that support the findings of this study are openly available.

Notes

  1. http://www.wfmc.org

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  1. Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, 221005, India

    Rambabu Medara & Ravi Shankar Singh

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  1. Rambabu Medara
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Energy-aware cloud workflow management system architecture proposed; Introduced various energy models for workflow scheduling techniques. scheduling techniques; Optimization objectives such as makespan, deadline, cost and energy-aware are studied; Survey conducted on recent techniques on “Energy-Aware Workflow Scheduling in IaaS Clouds”; Algorithms studied by considering various aspects such as evaluation environment, application model, scheduling paradigm, resource model and optimization techniques. item Future perspectives on the energy-aware workflow scheduling approaches are offered.

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Medara, R., Singh, R.S. A Review on Energy-Aware Scheduling Techniques for Workflows in IaaS Clouds. Wireless Pers Commun 125, 1545–1584 (2022). https://doi.org/10.1007/s11277-022-09621-1

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