CHAT: Accurate Network Latency Measurement for 5G E2E Networks

Abstract

As numerous latency-sensitive applications have emerged with the popularization of 5G networking, accurate and rapid end-to-end latency measurement has come to play an essential role in network fault diagnosis and optimization. Although the Bloom hash-based timestamp aggregation method has been reported to be scalable and efficient, two shortcomings that reduce its accuracy have yet to be fully considered: frequent hash collisions and its fixed measurement interval. To address these challenges, we construct an end-to-end network latency measurement framework named Cuckoo Hash Adjustive Table exchange (CHAT). By employing an improved cuckoo filter, we decrease the number of hash collisions to assess the latency more accurately. Moreover, CHAT adjusts the receiver-side measurement interval dynamically based on a gain indicator, maximizing the total number of valid packets used for latency estimation. Additionally, the proposed measurement framework minimizes the number of packets transferred over links to avoid interfering with the end-to-end latency measurement in an actual network. Finally, extensive experiments on simulations and a practical real-world environment show the effectiveness and applicability of CHAT.