An Economic Analysis of Cloud-Assisted Routing for Wider Area SDN

被引:4
作者
Dey, Prasun Kanti [1 ]
Yuksel, Murat [1 ]
机构
[1] Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA
来源
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT | 2020年 / 17卷 / 01期
基金
美国国家科学基金会;
关键词
Cloud computing; Routing; Economics; Random access memory; Automobiles; Scalability; Biological system modeling; Network economics; cloud computing; cloud pricing; SDN; routing; scalability;
D O I
10.1109/TNSM.2019.2947030
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid growth of the Internet traffic and the intensity of online transactions taking place, it is expected that the current routing needs careful modifications and smart innovations to ensure effective and reliable end-to-end packet delivery. This involves new feature developments for handling traffic with reduced latency to tackle routing scalability issues in a more secure way and to offer new services at cheaper cost. Considering the fact that prices of DRAM (Dynamic Random Access Memory) or TCAM (Ternary Content-Addressable Memory) in legacy routers are not necessarily decreasing at a desired pace, cloud computing can be a great solution to manage the increasing computation and memory complexity of routing functions in a centralized manner with optimized expenses. Such cloud integration to routing is becoming plausible as cloud providers now offer various pricing schemes and provide large-scale computing infrastructure to meet the users' choice. Focusing on the attributes associated with existing routing cost models and by exploring a hybrid approach to SDN, we compare recent trends in cloud pricing (for both storage and service) to evaluate whether it would be economically beneficial to integrate cloud services with legacy routing for improved cost-efficiency.
引用
收藏
页码:445 / 458
页数:14
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