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Open AccessFeature PaperArticle

Scheduling Fair Resource Allocation Policies for Cloud Computing through Flow Control

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Department of Applied Informatics, University of Macedonia, 54636 Thessaloniki, Greece
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Department of Production and Management Engineering, Democritus University of Thrace, 67100 Xanthi, Greece
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Author to whom correspondence should be addressed.
Electronics 2019, 8(11), 1348; https://doi.org/10.3390/electronics8111348
Received: 6 October 2019 / Revised: 4 November 2019 / Accepted: 9 November 2019 / Published: 14 November 2019
(This article belongs to the Section Computer Science & Engineering)
In this short paper, we discuss the problem of resource allocation for cloud computing. The cloud provides a variety of resources for users based on their requirements. Thus, one of the main issues in cloud computing is to design an efficient resource allocation scheme. Each job generated by a user in the cloud has some resource requirements. In this work, we propose a resource allocation method which aims at maximizing the resource utilization and distributing the system’s resources in a fast and fair way, by controlling the flow according to the resources available and by analyzing the dominant demands of each job. Moreover, by parallelizing the computations required, the runtime of the proposed strategy increases linearly as the number of jobs N increases. Here, we present some initial experimental results for small sets of users, that have shown that our strategy allocates the available resources among user jobs in a fair manner, while increasing the overall utilization of each resource. View Full-Text
Keywords: cloud computing; resource allocation; allocation cost; job generation control; big data; scheduling cloud computing; resource allocation; allocation cost; job generation control; big data; scheduling
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Souravlas, S.; Katsavounis, S. Scheduling Fair Resource Allocation Policies for Cloud Computing through Flow Control. Electronics 2019, 8, 1348.

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