Joint Computation Partitioning and Resource Allocation for Latency Sensitive Applications in Mobile Edge Clouds

Lei Yang, Bo Liu, Jiannong Cao, Yuvraj Sahni, Zhenyu Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

22 Citations (Scopus)


The proliferation of mobile devices and ubiquitous access of the wireless network enables many new mobile applications such as augmented reality, mobile gaming and so on. As the applications are latency sensitive, researchers propose to offload the complex computations of these applications to the nearby mobile edge cloud, in order to reduce the latency. Existing works mostly consider the problem of partitioning the computations between the mobile device and the traditional cloud that has abundant resources. The proposed approaches can not be applied in the context of mobile edge cloud, because both the resources in the mobile edge cloud and the wireless access bandwidth to the edge cloud are constrained. In this paper, we study joint computation partitioning and resource allocation problem for latency sensitive applications in mobile edge clouds. The problem is novel in that we combine the computation partitioning and the two-dimensional resource allocations in both the computation resources and the network bandwidth. We develop a new and efficient method, namely Multi-Dimensional Search and Adjust (MDSA), to solve the problem. We compares MDSA with the classic list scheduling method and the SearchAdjust algorithm via comprehensive simulations. The results show that MDSA outperforms the benchmark algorithms in terms of the overall application latency.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 10th International Conference on Cloud Computing, CLOUD 2017
EditorsGeoffrey C. Fox
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9781538619933
Publication statusPublished - 8 Sep 2017
Event10th IEEE International Conference on Cloud Computing, CLOUD 2017 - Honolulu, United States
Duration: 25 Jun 201730 Jun 2017

Publication series

NameIEEE International Conference on Cloud Computing, CLOUD
ISSN (Print)2159-6182
ISSN (Electronic)2159-6190


Conference10th IEEE International Conference on Cloud Computing, CLOUD 2017
Country/TerritoryUnited States


  • computation partitioning
  • latency sensitive applications
  • mobile edge cloud

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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