Virtual machine placement and workload assignment for mobile edge computing

As an extension to cloud computing, Mobile Edge Computing (MEC) provides computing capability at close proximity to mobile users to reduce service latency and improve users' quality of experience. In MEC, tiny datacenters, equipped with computing and storage capabilities, are located at the edg...

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Bibliographic Details
Published in2017 IEEE 6th International Conference on Cloud Networking (CloudNet) pp. 1 - 6
Main Authors Wei Wang, Yongli Zhao, Tornatore, Massimo, Gupta, Abhishek, Jie Zhang, Mukherjee, Biswanath
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Cloud computing
Collaboration
Delays
Edge computing
Hardware
Hardware consumption
Latency
Mobile communication
Mobile Edge Computing
Servers
VM placement
Workload assignment
Online AccessGet full text
DOI10.1109/CloudNet.2017.8071527

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Summary:As an extension to cloud computing, Mobile Edge Computing (MEC) provides computing capability at close proximity to mobile users to reduce service latency and improve users' quality of experience. In MEC, tiny datacenters, equipped with computing and storage capabilities, are located at the edge of the mobile network. Services in these tiny datacenters are supported by application-specific software instances, which are packaged in Virtual Machines (VM). We study the problem of VM placement and workload assignment for mobile cloud applications in MEC. We formulate a mathematical model to minimize the hardware consumption required by VMs for supporting given workloads in a multi-application scenario, while meeting heterogeneous latency requirements of different applications. Numerical results show that applications' latency requirement, MEC servers' hardware capacity, and users' request load have significant influences on overall hardware consumption, and MEC server utilization can be optimized by leveraging remote VM placement and workload aggregation.
DOI:10.1109/CloudNet.2017.8071527