Table of Contents Author Guidelines Submit a Manuscript
Mobile Information Systems
Volume 2016, Article ID 6146435, 7 pages
http://dx.doi.org/10.1155/2016/6146435
Research Article

An Optimal Routing Algorithm in Service Customized 5G Networks

1State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 199, No. 10, Xitucheng Road, Haidian District, Beijing 100876, China
2Beijing University of Posts and Telecommunications, P.O. Box 199, No. 10, Xitucheng Road, Haidian District, Beijing 100876, China
3Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, P.O. Box 199, No. 10, Xitucheng Road, Haidian District, Beijing 100876, China

Received 5 November 2015; Accepted 21 December 2015

Academic Editor: Xin Wang

Copyright © 2016 Haipeng Yao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

With the widespread use of Internet, the scale of mobile data traffic grows explosively, which makes 5G networks in cellular networks become a growing concern. Recently, the ideas related to future network, for example, Software Defined Networking (SDN), Content-Centric Networking (CCN), and Big Data, have drawn more and more attention. In this paper, we propose a service-customized 5G network architecture by introducing the ideas of separation between control plane and data plane, in-network caching, and Big Data processing and analysis to resolve the problems traditional cellular radio networks face. Moreover, we design an optimal routing algorithm for this architecture, which can minimize average response hops in the network. Simulation results reveal that, by introducing the cache, the network performance can be obviously improved in different network conditions compared to the scenario without a cache. In addition, we explore the change of cache hit rate and average response hops under different cache replacement policies, cache sizes, content popularity, and network topologies, respectively.