EMM: Energy-Aware Mobility Management for Mobile Edge Computing in Ultra Dense Networks



SOURCE  IEEE J. Sel. Areas Commun., Nov. 2017

Published Date:2017-11


Merging mobile edge computing (MEC) functionality with the dense deployment of base stations (BSs) provides enormous benefits such as a real proximity, ultra-low latency access to computing resources. However, the envisioned integration creates many new challenges, among which mobility management is a critical one. Simply applying existing radio access oriented mobility management schemes leads to poor performance due to the highly overlapped coverages of multiple BSs in the proximity of the user, and the co-provisioning of radio access and computing services of the MEC-enabled BSs. In this paper, we develop a novel user-centric energy-aware mobility management (EMM) scheme, in order to optimize the radio access and computation performance under the mobile user's long-term energy consumption constraint. Based on Lyapunov optimization and multi armed bandit theories, EMM works in an online fashion without requiring future system state information, and effectively handles the lack of exact environmental state information. Theoretical analysis explicitly takes BS handover and computation migration cost into consideration and gives a bounded deviation on both delay performance and energy consumption compared to the oracle solution with exact and complete future system information. The proposed algorithm also effectively handles the scenario in which candidate BSs vary during the offloading process of a task due to BS on/off. Simulations show that our proposed algorithms can achieve close-to-optimal delay performance while satisfying the energy consumption constraint.

This entry was posted in Publications and tagged , . Bookmark the permalink.

Comments are closed.