Scalable Resource Allocation Techniques for Edge Computing Systems

Caroline Rublein, Fidan Mehmeti, Taha D. Gunes, Sebastian Stein, Thomas F. La Porta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. We focus on a distributed resource allocation method in which servers operate independently and do not communicate with each other, but interact with clients (tasks) to make allocation decisions. This provides robustness and does not require service providers to share information about their configurations or workloads. We utilize a two-round bidding approach of assigning tasks to edge cloud servers. We consider a preemption-enabled system in which servers may stop a previous task in order to run a more useful one. We evaluate the performance of our system using realistic simulations and real-world trace data from a high-performance computing cluster. Results show that our approach is reasonably close to optimal assignment, while saving 50-70 % of the original computation time.

Original languageEnglish (US)
Title of host publicationICCCN 2022 - 31st International Conference on Computer Communications and Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665497268
DOIs
StatePublished - 2022
Event31st International Conference on Computer Communications and Networks, ICCCN 2022 - Virtual, Online, United States
Duration: Jul 25 2022Jul 27 2022

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
Volume2022-July
ISSN (Print)1095-2055

Conference

Conference31st International Conference on Computer Communications and Networks, ICCCN 2022
Country/TerritoryUnited States
CityVirtual, Online
Period7/25/227/27/22

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

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