It's hard to share: Joint service placement and request scheduling in edge clouds with sharable and non-sharable resources

Ting He, Hana Khamfroush, Shiqiang Wang, Tom La Porta, Sebastian Stein

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

17 Scopus citations

Abstract

Mobile edge computing is an emerging technology to offer resource-intensive yet delay-sensitive applications from the edge of mobile networks, where a major challenge is to allocate limited edge resources to competing demands. While prior works often make a simplifying assumption that resources assigned to different users are non-sharable, this assumption does not hold for storage resources, where users interested in services (e.g., data analytics) based on the same set of data/code can share storage resource. Meanwhile, serving each user request also consumes non-sharable resources (e.g., CPU cycles, bandwidth). We study the optimal provisioning of edge services with non-trivial demands of both sharable (storage) and non-sharable (communication, computation) resources via joint service placement and request scheduling. In the homogeneous case, we show that while the problem is polynomial-time solvable without storage constraints, it is NP-hard even if each edge cloud has unlimited communication or computation resources. We further show that the hardness is caused by the service placement subproblem, while the request scheduling subproblem is polynomial-time solvable via maximum-flow algorithms. In the general case, both subproblems are NP-hard. We develop a constant-factor approximation algorithm for the homogeneous case and efficient heuristics for the general case. Our trace-driven simulations show that the proposed algorithms, especially the approximation algorithm, can achieve near-optimal performance, serving 2-3 times more requests than a baseline solution that optimizes service placement and request scheduling separately.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE 38th International Conference on Distributed Computing Systems, ICDCS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages365-375
Number of pages11
ISBN (Electronic)9781538668719
DOIs
StatePublished - Jul 19 2018
Event38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018 - Vienna, Austria
Duration: Jul 2 2018Jul 5 2018

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2018-July

Other

Other38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018
CountryAustria
CityVienna
Period7/2/187/5/18

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

He, T., Khamfroush, H., Wang, S., La Porta, T., & Stein, S. (2018). It's hard to share: Joint service placement and request scheduling in edge clouds with sharable and non-sharable resources. In Proceedings - 2018 IEEE 38th International Conference on Distributed Computing Systems, ICDCS 2018 (pp. 365-375). (Proceedings - International Conference on Distributed Computing Systems; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCS.2018.00044