CourseCluster: A Distributed Course Registration System for Efficient Student Enrollment

In modern academic institutions, managing course registration efficiently is critical to student success. This paper presents CourseCluster, a distributed system designed to streamline university course registration. The system is built to support high-volume course searches and student registrations through a scalable web interface. Using data sets of courses and students, the system employs distributed nodes to process queries and manage registrations. Utilizing a MapReduce framework for search operations and a locking mechanism for registration, CourseCluster ensures atomicity and scalability. We also propose a search algorithm inspired by PageRank that integrates TF-IDF for enhanced search precision. Deployed on Amazon Web Services (AWS) for scalability, the system’s performance was evaluated, revealing its ability to handle high traffic loads with minimal latency. This work explores future improvements such as fault tolerance, machine learning-driven recommendations, and broader scalability to multiple universities. CourseCluster lays the foundation for more efficient and distributed education platforms in a globally connected academic environment.