Mobile edge computing (MEC) literally pushes cloud computing from remote datacenters to the life radius of end users. By leveraging the widely adopted European Telecommunications Standards Institute network function virtualization architecture, MEC provisions elastic and resilient mobile edge applications with proximity. Typical MEC virtualization infrastructure allows a configurable placement policy to deploy mobile edge applications as virtual machines (VMs): affinity can be used to put VMs on the same host for inter-VM networking performance, whereas anti-affinity is to separate VMs for high availability. In this paper, we propose a novel model to track the availability and cost impact from placement policy changes of the mobile edge applications. We formulate our model as a stochastic programming problem. To minimize the complexity challenge, we also propose a heuristic algorithm called EdgePlace. With our model, the unit resource cost increases when there are less resources left on a host. Applying affinity would take up more resources of the host but saves network bandwidth cost because of colocation. When enforcing anti-affinity, experimental results show increases of both availability and interhost network bandwidth cost. For applications with different resource requirements, our model is able to find their sweet points with the consideration of both resource cost and application availability, which is vital in a less robust MEC environment.
Transactions on Emerging Telecommunications Technologies
Department of Systems and Computer Engineering

Zhu, H. (He), & Huang, C. (2018). EdgePlace: Availability-aware placement for chained mobile edge applications. Transactions on Emerging Telecommunications Technologies. doi:10.1002/ett.3504