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EM: Energy efficient mobility management in dense small cells with mobile edge computing

机译:EM:具有移动边缘计算功能的密集型小型小区中的节能移动管理

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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. Simulation results show that our proposed scheme can significantly improve the computation performance (compared to state of the art) while satisfying the communication energy constraint.
机译:将移动边缘计算与小型基站的密集部署相结合,将带来巨大的好处,例如真正的邻近性,对云功能的超低延迟访问。但是,预想的集成带来了许多新的挑战,最重要的挑战之一就是移动性管理,这正成为整个系统性能的关键瓶颈。由于用户附近多个基站的覆盖区域高度重叠以及无线电接入和计算服务的共同提供,简单地应用现有解决方案会导致性能不佳。在本文中,我们利用Lyapunov优化和多臂土匪理论,开发了一种以用户为中心的新型移动性管理方案,以便在保持用户通信能耗低于约束的同时最大程度地提高用户的边缘计算性能。所提出的方案有效地处理了系统中多个级别上存在的不确定性,并提供了短期和长期的性能保证。仿真结果表明,我们提出的方案可以在满足通信能量约束的同时,显着提高计算性能(与现有技术相比)。

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