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UDRF: Multi-resource Fairness for Complex Jobs with Placement Constraints

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Title: UDRF: Multi-resource Fairness for Complex Jobs with Placement Constraints
Authors: Tahir
Yang
Koliousis
McCann
Item Type: Conference Paper
Abstract: In this paper, we study the problem of multi- resource fairness in systems running complex jobs that consist of multiple interconnected tasks. A job is considered finished when all its corresponding tasks have been executed in the system. Tasks can have different resource requirements. Because of special demands on particular hardware or software, tasks may have placement constraints limiting the type of machines they can run on. We develop User-Dependence Dominant Resource Fairness (UDRF), a generalized version of max-min fairness that combines graph theory and the notion of dominant re- source shares to ensure multi-resource fairness between complex workflows. UDRF satisfies several desirable properties including strategy proofness, which ensures that users do not benefit from misreporting their true resource demands. We propose an offline algorithm that computes optimal UDRF allocation. But optimality comes at a cost, especially for systems where schedulers need to make thousands of online scheduling decisions per second. Therefore, we develop a lightweight online algorithm that closely approximates UDRF. Besides that, we propose a simple mechanism to decentralize the UDRF scheduling process across multiple schedulers. Large-scale simulations driven by Google cluster-usage traces show that UDRF achieves better resource utilization and throughput compared to the current state-of-the-art in fair resource allocation.
Issue Date: 10-Dec-2015
Date of Acceptance: 2-Jul-2015
URI: http://hdl.handle.net/10044/1/24560
DOI: https://dx.doi.org/10.1109/GLOCOM.2015.7417010
Publisher: IEEE
Start Page: 1
End Page: 7
Journal / Book Title: 2015 IEEE Global Communications Conference (GLOBECOM)
Copyright Statement: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: IEEE GLOBECOM 2015
Publication Status: Published
Start Date: 2015-12-06
Finish Date: 2015-12-10
Conference Place: San Diego, CA
Appears in Collections:Computing
Faculty of Engineering