关键词: 网络带宽测量, 微内核, 泛在计算, 服务器无感知计算, 突发式快启动

Abstract: Next-generation mobile networks,represented by 5G/6G and WiFi 6/7,have substantially increased access bandwidth(i.e.,network speed).At the same time,they have also amplified fluctuations in network performance-such as throughput,latency,and packet loss-thereby prolonging speed tests,increasing traffic overhead,and degrading user experience.More importantly,this volatility makes it difficult to meet the pressing requirement for low-cost and highly real-time networking in microkernel-based ubiquitous computing systems(e.g.,MINIX,QNX,and seL4),where task management and inter-process communication critically depend on timely and lightweight network support.Although serverless computing built on cloud functions and cloud containers offers a potential solution path,existing rapid bandwidth measurement methods(e.g.,Swiftest) remain heavily constrained by the long-tail traffic effect,leading to considerable traffic waste.To address this challenge,this paper propose a serverless-based approach to fast measurement of network bandwidth.We first analyze the causes of the long-tail effect in prior approaches by combining transport-layer mechanism analysis with real-world measurement data.Building on these insights,we design a bursty fast-start transmission mechanism that decomposes the conventional smoothly ramped packet-sending strategy into multiple rounds of short-duration burst transmissions.With dynamic feedback from the client,the sender regulates its transmission rate in real time to shorten measurement duration and improve estimation accuracy,thereby avoiding long-tail traffic waste induced by delayed control feedback.Experiments across multiple representative network scenarios show that,compared with Swiftest,the proposed method reduces server-side transmitted traffic by 85% and shortens the average measurement time to 1.6 se-conds.These gains significantly alleviate server resource pressure and reduce client data consumption,while exhibiting strong engineering deployability in ubiquitous computing environments.

Key words: Network bandwidth measurement, Microkernel, Ubiquitous computing, Serverless computing, Bursty fast start