Cache Placement in Fog-RANs: From Centralized to Distributed Algorithms
Cache Placement in Fog-RANs: From Centralized to Distributed Algorithms
复制标题
Fog-RAN 中的缓存放置：从集中式算法到分布式算法
DOI：
10.1109/twc.2017.2737015
复制
发表时间：
2017-11-01
影响因子：
10.4
通讯作者：
Letaief, Khaled B.
中科院分区：
文献类型：
--
作者：
Liu, Juan;Bai, Bo;Letaief, Khaled B.
为了应对大规模移动的用户的高速和/或超低延迟数据业务的快速增长，雾无线电接入网络（Fog-RAN）已经成为下一代无线网络的有前途的架构。在Fog-RAN中，边缘节点和用户终端具有不同程度的存储、计算和通信功能，这为网络操作提供了高度灵活性，即，从完全集中到完全分散。在本文中，我们研究了该高速缓存放置在Fog-RAN的问题，考虑到灵活的物理层传输方案和不同的用户的不同内容偏好。我们开发了集中式和分布式传输感知缓存放置策略，以最大限度地减少用户的平均下载延迟的存储容量的限制。在集中式模式下，将该高速缓存放置问题转化为拟阵约束下的子模极大化问题，并提出了一种在常数因子内寻找最优解的近似算法.在分布式模式下，提出了一种基于信念传播的分布式算法，以提供一个次优的解决方案，在每个BS的基础上，本地收集的信息进行迭代更新。仿真结果表明，通过利用缓存和合作增益，所提出的传输感知缓存算法可以大大降低用户的平均下载延迟。
To deal with the rapid growth of high-speed and/or ultra-low latency data traffic for massive mobile users, fog radio access networks (Fog-RANs) have emerged as a promising architecture for next-generation wireless networks. In Fog-RANs, the edge nodes and user terminals possess storage, computation and communication functionalities to various degrees, which provide high flexibility for network operation, i.e., from fully centralized to fully distributed operation. In this paper, we study the cache placement problem in Fog-RANs, by taking into account flexible physical-layer transmission schemes and diverse content preferences of different users. We develop both centralized and distributed transmission aware cache placement strategies to minimize users’ average download delay subject to the storage capacity constraints. In the centralized mode, the cache placement problem is transformed into a matroid constrained submodular maximization problem, and an approximation algorithm is proposed to find a solution within a constant factor to the optimum. In the distributed mode, a belief propagation-based distributed algorithm is proposed to provide a suboptimal solution, with iterative updates at each BS based on locally collected information. Simulation results show that by exploiting caching and cooperation gains, the proposed transmission aware caching algorithms can greatly reduce the users’ average download delay.