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arXiv 2512.04089cs.DC
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无服务器 everywhere：浏览器、边缘和云上WebAssembly工作流的比较分析

Serverless Everywhere: A Comparative Analysis of WebAssembly Workflows Across Browser, Edge, and Cloud

MIFT Department, University of Messina（墨西拿大学 MIFT 系）；Institute of Information Technology, University of Klagenfurt（克拉根福大学信息技术研究所）；Center for Ubiquitous Computing, University of Oulu（奥卢大学泛在计算中心）；Department of Computer Science, University of Innsbruck（因斯布鲁克大学计算机科学系）

Mario Colosi, Reza Farahani, Lauri Loven, Radu Prodan, Massimo Villari

备注：
7 pages, 8 Figures, 2 Tables, conference paper
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AI总结：

本文比较了浏览器、边缘和云环境中WebAssembly工作流的性能，发现AOT编译和预热显著降低启动延迟，浏览器在小负载下表现优异，但随着负载增大，边缘和云节点的AOT执行更优。

摘要：

WebAssembly（Wasm）是一种二进制指令格式，它使可以在异构平台上实现便携、沙箱化和接近原生的执行，使其非常适合在浏览器、边缘节点和云服务器上执行无服务器工作流。然而，其性能和稳定性严重依赖于诸如启动开销、运行时执行模型（例如，提前编译（AOT）和即时编译（JIT）编译）以及部署环境中的资源变化等因素。本文评估了一个基于Wasm的无服务器工作流在浏览器到边缘和云实例中的一致执行。该设置使用wasm32-wasi模块：在浏览器中，执行发生在Web worker中，而在边缘和云中，一个HTTP shim将帧流式传输到Wasm运行时。我们测量冷启动和热启动延迟、每步骤延迟、工作流总时长、吞吐量以及CPU/内存利用率，以捕捉跨环境的端到端行为。结果表明，AOT编译和实例预热显著减少了启动延迟。对于具有小负载的工作流，浏览器由于完全内存中的数据交换而实现竞争性性能。相比之下，随着负载增长，工作流进入计算和内存密集型阶段，其中边缘和云节点上的AOT执行明显优于浏览器性能。

英文摘要：

WebAssembly (Wasm) is a binary instruction format that enables portable, sandboxed, and near-native execution across heterogeneous platforms, making it well-suited for serverless workflow execution on browsers, edge nodes, and cloud servers. However, its performance and stability depend heavily on factors such as startup overhead, runtime execution model (e.g., Ahead-of-Time (AOT) and Just-in-Time (JIT) compilation), and resource variability across deployment contexts. This paper evaluates a Wasm-based serverless workflow executed consistently from the browser to edge and cloud instances. The setup uses wasm32-wasi modules: in the browser, execution occurs within a web worker, while on Edge and Cloud, an HTTP shim streams frames to the Wasm runtime. We measure cold- and warm-start latency, per-step delays, workflow makespan, throughput, and CPU/memory utilization to capture the end-to-end behavior across environments. Results show that AOT compilation and instance warming substantially reduce startup latency. For workflows with small payloads, the browser achieves competitive performance owing to fully in-memory data exchanges. In contrast, as payloads grow, the workflow transitions into a compute- and memory-intensive phase where AOT execution on edge and cloud nodes distinctly surpasses browser performance.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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