Asymmetric network information cache based on mobile traffic in software-defined network

• Main Authors: Liang Hu, Jiejun Hu, Tao Fu, Jiyang Bao, Feng Wang
• Format: Article
• Language: English
• Published: SAGE Publishing 2019-01-01
• Series: Advances in Mechanical Engineering
• Online Access: https://doi.org/10.1177/1687814018819894

Software-defined network is an encouraging research area that realizes updates throughout an entire network, and a wireless network is ubiquitous in an up-to-date world. The combination of these techniques, which is referred to as a wireless software-defined network, has been a significant development in numerous testbeds. The extensive use of distributed controllers that achieved elastic extension and are fault tolerant in large-scale wireless networks is hopeful. Despite their profits, they generate significant overhead in synchronizing network information. Thus, power-hungry wireless software-defined network devices limit the usage of distributed controllers in wireless networks. The patterns of storing network information have a crucial effect on controller performances, as they determine the probability of processing requests based on local data. To address this problem, we identify a better pattern for controllers to retain proper network information to balance costs in terms of both synchronous traffic and response time. We analyze the characteristics of distributed controllers and propose an overhead model of a distributed controller in a wireless software-defined network. Based on this model, we design an asymmetric network information cache to make trade-offs among different controller architectures. The asymmetric network information cache measures real-time network traffic and computes the traffic among sub-networks controlled by controller nodes. Then, the controller asymmetrically caches suitable network data to substantially busier nodes. The experimental results indicate that the asymmetric network information cache achieves a trade-off between synchronous traffic and the average response time.