4.7 Article Proceedings Paper

C-RoFN: Multi-Stratum Resources Optimization for Cloud-Based Radio over Optical Fiber Networks

期刊

IEEE COMMUNICATIONS MAGAZINE
卷 54, 期 8, 页码 118-125

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/mcom.2016.7537186

关键词

-

向作者/读者索取更多资源

C-RAN has become a promising scenario to accommodate high-performance services, which provides ubiquitous user coverage and supports real-time cloud computing using cloud BBUs. The interaction between RRH and BBU or resource schedule among BBUs in cloud have become more frequent and complex due to the development of system-scale and user requirements. The heavy-duty interaction can promote the networking demand among RRHs and BBUs, and forces to form elastic optical fiber switching and optical networking according to the characteristics of high bandwidth, low cost, and transparent multi-rate traffic transmission. In such a network, the multiple stratum resources of radio, optical, and BBU processing unit have interwoven with each other, so the traditional architecture cannot efficiently implement the resource optimization and scheduling for the high-level QoS guarantee. In this article, we present a novel C-RoFN architecture for MSRO using software defined networking. The proposed architecture can globally optimize radio frequency, optical spectrum, and BBU processing resources effectively to maximize radio coverage and meet the QoS requirement. The functional modules of C-RoFN architecture, including the core elements of radio, optical, and BBU controllers, are described in detail. The cooperation procedures in multi-layer vertical integration and cross-stratum horizontal merging models are investigated. The overall feasibility and efficiency of the proposed architecture are also experimentally demonstrated on our SDN-enabled testbed with OpenFlow-enabled elastic optical nodes, and compared to cross-stratum optimization strategy in terms of resource occupation and path provisioning latency. Numerical results are given and analyzed based on the testbed. Some future discussions are presented in the conclusion.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据