Edge User Allocation with Dynamic Quality of Service

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11895)


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.


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



This research is funded by Australian Research Council Discovery Projects (DP170101932 and DP18010021).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Swinburne University of TechnologyHawthornAustralia
  2. 2.Deakin UniversityBurwoodAustralia
  3. 3.Monash UniversityClaytonAustralia
  4. 4.The University of AucklandAucklandNew Zealand

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