On cost aware cloudlet placement for mobile edge computing

Qiang Fan, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


As accessing computing resources from the remote cloud inherently incurs high end-to-end (E2E)delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost (i.e., consisting of both the cloudlet cost and average E2E delay cost)has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing (CAPABLE)strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations.

Original languageEnglish (US)
Article number8753750
Pages (from-to)926-937
Number of pages12
JournalIEEE/CAA Journal of Automatica Sinica
Issue number4
StatePublished - Jul 2019

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering


  • Cloudlet placement
  • Mobile cloud computing
  • Mobile edge computing


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