Edge user allocation with dynamic quality of service

Phu Lai, Qiang He, Guangming Cui, Xiaoyu Xia, Mohamed Abdelrazek, Feifei Chen, John Hosking, John Grundy, Yun Yang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

24 Citations (Scopus)


In edge computing, edge servers are placed in close proximity to end-users. App vendors can deploy their services on edge servers to reduce network latency experienced by their app users. The edge user allocation (EUA) problem challenges service providers with the objective to maximize the number of allocated app users with hired computing resources on edge servers while ensuring their fixed quality of service (QoS), e.g., the amount of computing resources allocated to an app user. In this paper, we take a step forward to consider dynamic QoS levels for app users, which generalizes but further complicates the EUA problem, turning it into a dynamic QoS EUA problem. This enables flexible levels of quality of experience (QoE) for app users. We propose an optimal approach for finding a solution that maximizes app users’ overall QoE. We also propose a heuristic approach for quickly finding sub-optimal solutions to large-scale instances of the dynamic QoS EUA problem. Experiments are conducted on a real-world dataset to demonstrate the effectiveness and efficiency of our approaches against a baseline approach and the state of the art.

Original languageEnglish
Title of host publicationService-Oriented Computing
Subtitle of host publication17th International Conference, ICSOC 2019 Toulouse, France, October 28–31, 2019 Proceedings
EditorsSami Yangui, Ismael Bouassida Rodriguez, Khalil Drira, Zahir Tari
Place of PublicationCham Switzerland
Number of pages16
ISBN (Electronic)9783030337025
ISBN (Print)9783030337018
Publication statusPublished - 2019
EventInternational Conference on Service Oriented Computing 2019 - Toulouse, France
Duration: 28 Oct 201931 Oct 2019
Conference number: 17th

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Service Oriented Computing 2019
Abbreviated titleICSOC 2019
Internet address


  • Edge computing
  • Quality of Experience
  • Quality of Service
  • Resource allocation
  • User allocation

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