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Merging mobile edge computing with the dense deployment of small cell basestations promises enormous benefits such as a real proximity, ultra-low latencyaccess to cloud functionalities. However, the envisioned integration createsmany new challenges and one of the most significant is mobility management,which is becoming a key bottleneck to the overall system performance. Simplyapplying existing solutions leads to poor performance due to the highlyoverlapped coverage areas of multiple base stations in the proximity of theuser and the co-provisioning of radio access and computing services. In thispaper, we develop a novel user-centric mobility management scheme, leveragingLyapunov optimization and multi-armed bandits theories, in order to maximizethe edge computation performance for the user while keeping the user'scommunication energy consumption below a constraint. The proposed schemeeffectively handles the uncertainties present at multiple levels in the systemand provides both short-term and long-term performance guarantee. Simulationresults show that our proposed scheme can significantly improve the computationperformance (compared to state of the art) while satisfying the communicationenergy constraint.

E2M2: Energy Efficient Mobility Management in Dense Small Cells with Mobile Edge Computing