A&B: AI and Block-Based TCAM Entries Replacement Scheme for Routers
A&B: AI and Block-Based TCAM Entries Replacement Scheme for Routers
复制标题
A
DOI：
10.1109/jsac.2022.3191351
复制
发表时间：
2022-09
影响因子：
16.4
通讯作者：
Ke Xu
中科院分区：
文献类型：
--
作者：
Peizhuang Cong;Yuchao Zhang;Bin Liu;Wendong Wang;Zehui Xiong;Ke Xu
With the ever-increasing deployment of 5G and IoT, the number of end-hosts/terminals is increasing rapidly, so that routers have to cache more and more forwarding entries to guarantee communication reachability of these terminals, which makes Ternary Content Addressable Memory (TCAM)-based routers keep expanding resource requirements. However, the design and implementation of large-capacity TCAM-based routers are faced with such challenges: difficult circuit design, high production cost and energy consumption, thereby posing an urgent requirement on a lightweight TCAM that can still maintain those massive communication connections. In this paper, we aim to design a lightweight router with small storage requirement while still retaining the original communication connection performance, which is not straightforward due to the following two challenges: First, under the condition of massive sequential flow data, it’s difficult to accurately and timely select the entries to cache for a small capacity TCAM. Second, given the strict prefix matching principle, how to efficiently insert the selected entries into TCAM is also challenging. To address these problems, we propose A&B: an AI-based Routing entry prediction strategy (AIR) and a Block-based entry Insertion Tactic (BIT). AIR can precisely select entries by conducting accurate entry predictions, which converts dynamic flow-based prediction into stable and parallelizable entry-based prediction by decoupling spatio-temporal characteristics. BIT optimizes entry insertion by isolating TCAM into several blocks, thus eliminating the time-consuming entry movements. The experiment results based on real backbone traffic show that our lightweight A&B achieves comparable performance compared to the traditional schemes by using only 1/8 TCAM storage.
登录
查看更多内容
影响因子：
2.8
作者：
Tong Yang;Gaogang Xie;Yanbiao Li;Qiaobin Fu;A. Liu;Qi Li;L. Mathy
通讯作者：
Tong Yang;Gaogang Xie;Yanbiao Li;Qiaobin Fu;A. Liu;Qi Li;L. Mathy
DOI：
10.1109/49.772439
发表时间：
1999-06
期刊：
IEEE J. Sel. Areas Commun.
影响因子：
--
作者：
S. Nilsson;G. Karlsson
通讯作者：
S. Nilsson;G. Karlsson
DOI：
10.1145/1080091.1080115
发表时间：
2005-08
期刊：
--
影响因子：
--
作者：
K. Lakshminarayanan;Anand Rangarajan;S. Venkatachary
通讯作者：
K. Lakshminarayanan;Anand Rangarajan;S. Venkatachary
DOI：
10.1109/infocom41043.2020.9155281
发表时间：
2020-07
期刊：
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
影响因子：
--
作者：
Bohan Zhao;Rui Li;Jin Zhao;T. Wolf
通讯作者：
Bohan Zhao;Rui Li;Jin Zhao;T. Wolf
DOI：
10.1109/tnet.2015.2407831
发表时间：
2016-04
期刊：
IEEE/ACM Transactions on Networking
影响因子：
--
作者：
Kirill Kogan;S. Nikolenko;Ori Rottenstreich;W. Culhane;P. Eugster
通讯作者：
Kirill Kogan;S. Nikolenko;Ori Rottenstreich;W. Culhane;P. Eugster