Optimizing Backend Interactions in Microservices via Latency-Aware Design for Scalable Cloud Systems

Abstract

This study designs a human-computer interaction system for integrated ship navigation guidance based on data-mining technologies. The system accurately extracts effective navigation information to support safe and reliable ship navigation. By collecting both navigation and environmental data, the method employs adaptive K-means clustering to mine critical guidance features and construct an optimal navigation information set. The resulting guidance information is used to build a maritime environment map, while an improved genetic algorithm is applied to generate optimal ship-route plans and produce real-time guidance commands. Through the control and display module, the system outputs intuitive navigation-control results, enabling efficient human-computer interaction. Experimental results demonstrate that the proposed system effectively supports integrated ship-navigation guidance, accurately extracts key navigation and environmental information, optimizes route planning, avoids obstacles, and ensures navigation safety.