论文标题
在层次雾计算C-RAN网络中，任务卸载的延迟最小化
Latency Minimization for Task Offloading in Hierarchical Fog-Computing C-RAN Networks
论文作者
论文摘要
FOG计算网络结合了配备移动边缘计算（MEC）服务器的云计算和雾接入点（FAP），以支持移动用户的计算密集型任务。但是，由于FAP具有有限的计算功能，并且仅由云无线电访问（C-RAN）网络的基带处理单元（BBU）中的远程云中心提供帮助，因此该FOG计算的C-RAN网络的延迟益处可能会在面对大量的卸载请求时磨损。在本文中，我们调查了在层次雾计算的C-RAN网络中任务卸载的延迟最小化问题，该网络由三层计算服务组成：电台单元中的MEC服务器，分布式单元中的MEC服务器以及中央单元中的云计算。通过求解配制的混合整数编程问题，优化了每个服务器中卸载任务的接收波束成形向量，任务分配，用于卸载任务的计算速度以及Fronthaul链接的传输带宽分配。模拟结果验证了所提出的分层雾化C-RAN网络的优势，从延迟性能方面。
Fog-computing network combines the cloud computing and fog access points (FAPs) equipped with mobile edge computing (MEC) servers together to support computation-intensive tasks for mobile users. However, as FAPs have limited computational capabilities and are solely assisted by a remote cloud center in the baseband processing unit (BBU) of the cloud radio access (C-RAN) network, the latency benefits of this fog-computing C-RAN network may be worn off when facing a large number of offloading requests. In this paper, we investigate the delay minimization problem for task offloading in a hierarchical fog-computing C-RAN network, which consists of three tiers of computational services: MEC server in radio units, MEC server in distributed units, and the cloud computing in central units. The receive beamforming vectors, task allocation, computing speed for offloaded tasks in each server and the transmission bandwidth split of fronthaul links are optimized by solving the formulated mixed integer programming problem. The simulation results validate the superiority of the proposed hierarchical fog-computing C-RAN network in terms of the delay performance.
