چكيده به لاتين
Mobile edge computing has received an increasing amount
of attentions in recent years. A central theme of many prior
studies is offloading policies, i.e. what/when/how to offload a
user’s workload from its device to the edge system or cloud. Our paper does not
study offloading policies. There is also extensive work on dense small
cell networks, mainly focusing on radio resource management
and interference mitigation. Our paper does not
impose any assumption on how the network is planned or
how the radio resource is allocated among the cells (hence we
allow inter-cell interference in our model).
Merging mobile edge computing with the dense
deployment of small cell base stations promises enormous benefits
such as a real proximity, ultra-low latency access to cloud
functionalities. However, the envisioned integration creates many
new challenges and one of the most significant is mobility
management, which is becoming a key bottleneck to the overall
system performance. Simply applying existing solutions leads to
poor performance due to the highly overlapped coverage areas
of multiple base stations in the proximity of the user and the
co-provisioning of radio access and computing services. In this
paper, we develop a novel user-centric mobility management
scheme, leveraging Lyapunov optimization and multi-armed
bandits theories, in order to maximize the edge computation
performance for the user while keeping the user’s communication
energy consumption below a constraint. The proposed scheme
effectively handles the uncertainties present at multiple levels
in the system and provides both short-term and long-term performance guarantee.
Keywords: Lyapunov, Multi-armed bandits, Mobile Edge Computing, Mobility
Management, Energy Consumption, Ultra Dense Networking
