Reinforcement-Learning-based Foresighted Task Scheduling in Cloud Computing

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Mostafavi Seyedakbar; AHMADI FATEMEH; AGHA SARRAM MEHDI

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Journal Paper

Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2020 | Volume:50 | Issue:1 (91) Page(s): 387-401

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Information Journal Paper

Title

Reinforcement-Learning-based Foresighted Task Scheduling in Cloud Computing

Author(s)

Mostafavi Seyedakbar | AHMADI FATEMEH | AGHA SARRAM MEHDI | Issue Writer Certificate

Keywords

Cloud computingQ1

Task schedulingQ1

Reinforcement learningQ2

Foresighted task schedulingQ1

Response timeQ2

Abstract

With the apperance of cloud computing, users receive computing resources according to pay as you go of cloud service provider. An optimized scheduling approach for mapping all the tasks to the resources is an essential problem due to the limitations and dynamics of resources for requests which vary during the time. This solution may lead to improvement of system's efficiency. There are different methods for cloud computing scheduling with different parameters such as response time, makespan, waiting time, energy consumption, cost, utilization rate, and load balancing. But many of these methods are not suitable for improving scheduling performance in a condition that users requests change during the time. So in this thesis a scheduling method based on reinforcement learning is proposed. Adopting with environment conditions and responding to unsteady requests, reinforcement learning can cause a long-term increase in system's performance. The results show that this proposed method can not only reduce the response time and makespan but also increase resource efficiency as a minor goal. Our proposed illustrates improvements in response time for 49. 52%, 46. 03%, 43. 99%, 43. 53% and 38. 68% over Random, Mix, FIFO, Greedy and Q-sch algorithms, respectively.

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APA: Copy

Mostafavi, Seyedakbar, AHMADI, FATEMEH, & AGHA SARRAM, MEHDI. (2020). Reinforcement-Learning-based Foresighted Task Scheduling in Cloud Computing. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 50(1 (91) ), 387-401. SID. https://sid.ir/paper/401782/en

Vancouver: Copy

Mostafavi Seyedakbar, AHMADI FATEMEH, AGHA SARRAM MEHDI. Reinforcement-Learning-based Foresighted Task Scheduling in Cloud Computing. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2020;50(1 (91) ):387-401. Available from: https://sid.ir/paper/401782/en

IEEE: Copy

Seyedakbar Mostafavi, FATEMEH AHMADI, and MEHDI AGHA SARRAM, “Reinforcement-Learning-based Foresighted Task Scheduling in Cloud Computing,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 50, no. 1 (91) , pp. 387–401, 2020, [Online]. Available: https://sid.ir/paper/401782/en

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