SegMobaTree: The Segmented Multilayer Online Balanced Tree for high-performance IPv6 Lookup in the Edge Network

TL;DR

SegMobaTree introduces a multilayer online balanced tree structure optimized for high-speed IPv6 lookup in edge networks, outperforming existing algorithms in speed and memory efficiency.

Contribution

The paper proposes SegMobaTree, a novel segmented multilayer balanced tree algorithm that improves IPv6 lookup performance and update speed for edge networks.

Findings

Achieves 1.5x to 1.7x faster lookup speed than SAIL, Poptrie, and Hi-BST.

Provides 11.8x to 32.8x faster update speed compared to baseline algorithms.

Uses dynamic programming to optimize prefix segmentation, balancing tree scale and performance.

Abstract

With the development of IPv6 and edge computing, the edge network should support IPv6 lookup (the longest prefix matching, LPM) with high lookup speed, high update speed, and low memory cost. However, the trie-based algorithms, e.g., SAIL and Poptrie, mainly focus on the IPv4 ruleset but have disadvantages in the edge IPv6 ruleset with longer prefix length. The binary-based algorithm Hi-BST also has limited lookup speed with too many memory accesses. Therefore, we propose the SegMobaTree algorithm to achieve high-performance IPv6 lookup in the edge network. First, MobaTree is a multilayer online balanced tree to perform high-speed binary search among rules with different prefix lengths. Second, to avoid one large tree, we propose the dynamic programming method to split prefix lengths into a few suitable segments, which tradeoff between the number of segments and the scale of trees. Compared to SAIL, Poptrie, and Hi-BST, SegMobaTree achieves 1.5x, 1.7x, 1.6x lookup speed and 11.8x, 32.8x, 1.3x update speed with low memory cost.