Project Description:

Cloud computing can be leveraged to bridge the gap between the increasing complexity of mobile applications and the limited capabilities of mobile devices, by remotely executing mobile applications at the cloud. However, the efficiency of such remote execution is hindered by excessive network latency accessing data centers and significant overhead of provisioning and managing large amounts of Virtual Machines (VMs). Traditional solutions reduce the cloud access latency by deploying servers at the network edge, but ignore the impact of mobile users' workload patterns on the efficiency of cloud operation. Instead, this project aims to design the edge cloud as a tree hierarchy of geo-distributed servers, so as to efficiently exploit the cloud resources for handling the peak load from mobile users. This research will benefit end users with various mobile devices by facilitating practical integration of these devices into the cloud. The results from this research are likely to foster new research directions on edge cloud design and mobile cloud computing. The project will engage under-represented students in the research activities, and the scholarly discovery of this project will be disseminated broadly to the community.

This project aims to satisfy the performance requirements of remote program execution by designing the edge cloud in a hierarchical manner and hence ensuring efficient utilization of cloud resources. More specifically, this project consists of three closely intertwined research thrusts: (i) developing algorithms and systems to optimize the placement of mobile workloads among edge cloud servers and efficiently serve the mobile peak load; ii) mitigating the impact of user mobility on the performance of remote program execution, by developing efficient mobility-aware VM migration techniques; iii) developing an experimental testbed, as a unique research facility, to emulate and investigate the impact of mobile workload peak on edge cloud operations.

 

Selected publications (Complete List):

  1. Interconnecting Heterogeneous Devices in the Personal Mobile Cloud [pdf]
    Yong Li and Wei Gao, in Proceedings of the 36th IEEE Conference on Computer Communications (INFOCOM), 2017.
    (Acceptance Ratio: 292/1395=20.9%)

  2. Minimizing Context Migration in Mobile Code Offload [pdf]
    Yong Li and Wei Gao, IEEE Transactions on Mobile Computing, vol. 16(4), 2017, pp. 1005-1018.

  3. A Hierarchical Edge Cloud Architecture for Mobile Computing [pdf]
    Liang Tong, Yong Li and Wei Gao, in Proceedings of the 35th IEEE Conference on Computer Communications (INFOCOM), 2016.
    (Acceptance Ratio: 300/1644=18.25%)

 

Participants:

 

Software:

Under development. As project goes on, more information will be available.


This material is based upon work supported by the National Science Foundation under Grant No. 1527612. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).