Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds

Vajiheh Farhadi, Fidan Mehmeti, Ting He, Tom La Porta, Hana Khamfroush, Shiqiang Wang, Kevin S. Chan

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

138 Scopus citations


Mobile edge computing allows wireless users to exploit the power of cloud computing without the large communication delay. To serve data-intensive applications (e.g., augmented reality, video analytics) from the edge, we need, in addition to CPU cycles and memory for computation, storage resource for storing server data and network bandwidth for receiving user-provided data. Moreover, the data placement needs to be adapted over time to serve time-varying demands, while considering system stability and operation cost. We address this problem by proposing a two-time-scale framework that jointly optimizes service (data code) placement and request scheduling, under storage, communication, computation, and budget constraints. We fully characterize the complexity of our problem by analyzing the hardness of various cases. By casting our problem as a set function optimization, we develop a polynomial-time algorithm that achieves a constant-factor approximation under certain conditions. Extensive synthetic and trace-driven simulations show that the proposed algorithm achieves 90% of the optimal performance.

Original languageEnglish (US)
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781728105154
StatePublished - Apr 2019
Event2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France
Duration: Apr 29 2019May 2 2019

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference2019 IEEE Conference on Computer Communications, INFOCOM 2019

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


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