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Distributing Dynamic Divisible Loads
KTH, School of Electrical Engineering (EES), Network and Systems engineering.
KTH, School of Electrical Engineering (EES), Network and Systems engineering.
2017 (English)In: 2017 IFIP Networking Conference (IFIP Networking) and Workshops, Institute of Electrical and Electronics Engineers (IEEE), 2017Conference paper, Published paper (Refereed)
Abstract [en]

With the emergence of computing infrastructures in the cloud or at the network edge we need to address the question of how to utilize these shared resources when computational tasks are generated dynamically. While small computing tasks may be satisfied with the computing capacity of a single resource, large tasks may want to utilize multiple computing nodes and perform parallel processing to shorten the task completion time. In this paper we evaluate how additional overhead in such divisible load systems affect the efficiency of parallel processing - from the point of view of the task itself, and for the entire resource sharing system. We show that the preference of a single task may be in conflict with the allocation needed for a social optimum, which in turn depends heavily on the load as well as on the system size.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017.
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:kth:diva-224116DOI: 10.23919/IFIPNetworking.2017.8264889ISI: 000425452000066Scopus ID: 2-s2.0-85050469466ISBN: 9783901882944 (print)OAI: oai:DiVA.org:kth-224116DiVA, id: diva2:1190424
Conference
IFIP Networking Conference (IFIP Networking), June 12-16, 2017, Stockholm, Sweden
Note

QC 20180314

Available from: 2018-03-14 Created: 2018-03-14 Last updated: 2018-08-30Bibliographically approved

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Zeng, Ming

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  • apa
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  • nn-NB
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  • Other locale
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Output format
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