Enabling Stateful TCP Performance Profiling With Key Event Capturing

Abstract

TCP ensures reliable transmission through its stateful implementation and remains crucial today. TCP performance profiling is essential for tasks like diagnosing network performance problems, optimizing transmission performance, and developing new TCP variants, etc. Existing profiling methods lack enough attention to TCP state transition to provide detailed insights on TCP performance. Thus, we build TcpSight, a tool focusing on TCP state transition throughout connection lifetimes. TcpSight conducts stateful analysis by capturing key events using an efficient per-connection lock-free data management mechanism. Besides, TcpSight enhances profiling by integrating application layer information collected from the TCP stack. With the profiling results, users can identify the culprit of TCP performance degradation, and evaluate the performance of TCP algorithms. We design optional modules and filtering mechanisms to reduce TcpSight’s overhead. Our evaluation presents that TcpSight incurs an additional CPU consumption of about 16.6% (without filtering) and 10.6% (with filtering) when the server’s load is 55.7%, and generates storage consumption about 1.88 KB per connection on average. We also give application cases of TcpSight and the deployment experiences in Alibaba Cloud. TcpSight helps in revealing meaningful findings and insights into exploiting TCP in the production deployment.