High Load Elective System Design And Optimization

Course Selection System as an important component of Educational Administration Elective System, has been spun off from the traditional manual mode, with the rapid development of information technology, the online course selection system has become the main form of college enrollment. The Online Course Selection System has been improving the efficiency of the system by avoiding human error in manual mode and greatly reducing the workload of academic staff. In the other hand, with the Online Course Selection System, students have more selection and it seems much fair. However, with the constant expansion of college enrollment, the time of choosing course is in the same time and the number of choosing course are so many, the Server response of the Online Course Selection System becomes so slowly, the Online Course Selection System can't bear high-load weight, and it even happens server downtime phenomenon. Although by improving the hardware, or improve the course selection algorithm can improve the efficiency of the system to some extent, and more schools have adopted the method by time for students to choose courses. These methods are either costly, or let the students lost the fair, these are neither the good methods.This article from the application code and Web server two sides improve the Server of the system when there are a large amount of online access in the burst. In the application code, using the SOA development model to reduce the coupling between system modules, and enhancing the robustness and reusability of code, and can greatly accelerate the speed of system development, this paper uses Struts2-Spring-iBatis integration framework to achieve the MVC design pattern of the Course System; in Web Server, by tuning the performance of itself and the external conditions improves the Server response speed. and according to the characteristics of the Course System, we apply the Web server clustering and load balancing to meet the High-load applications.At the end of the article, we test the optimized online course selection system in high load conditions and observe the results. we can see that its performance has a good optimization.