Joint uplink/downlink optimization for backhaul-limited mobile cloud computing with user scheduling

Ali Al-Shuwaili, Osvaldo Simeone, Alireza Bagheri, Gesualdo Scutari

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Mobile cloud computing enables the offloading of computationally heavy applications, such as for gaming, object recognition or video processing, from mobile users (MUs) to cloudlet or cloud servers, which are connected to wireless access points, either directly or through finite-capacity backhaul links. In this paper, the design of a mobile cloud computing system is investigated by proposing the joint optimization of computing and communication resources with the aim of minimizing the energy required for offloading across all MUs under latency constraints at the application layer. The proposed design accounts for multiantenna uplink and downlink interfering transmissions, with or without cooperation on the downlink, along with the allocation of backhaul and computational resources and user selection. The resulting design optimization problems are nonconvex, and stationary solutions are computed by means of successive convex approximation techniques. Numerical results illustrate the advantages in terms of energy-latency tradeoff of the joint optimization of computing and communication resources, as well as the impact of system parameters, such as backhaul capacity, and of the network architecture.

Original languageEnglish (US)
Article number7850968
Pages (from-to)787-802
Number of pages16
JournalIEEE Transactions on Signal and Information Processing over Networks
Volume3
Issue number4
DOIs
StatePublished - Dec 2017

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Computer Networks and Communications

Keywords

  • 5G
  • Application offloading
  • backhaul
  • cloudlet
  • latency
  • mobile cloud computing
  • network MIMO
  • successive convex approximation
  • user selection

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