Research On Service Optimization Of Campus Big Data Platform

Campus management is mainly to solve the problems of daily management and teaching management,to achieve the purpose of promoting the development of the school,improving the teaching level and the efficiency of education management.In the process of campus platform management,a large number of behavior data and teaching data are produced.For take full advantage of these campus data,promote the improvement of teaching and enhance the comprehensive competitiveness of schools,big data technology is introduced to form the platform management based on campus big data.These generated behavior data and teaching data are collected,preprocessed,stored and analyzed,and sorted into effective information to provide improvement direction for service optimization of campus platform management.Combined with big data technology,a continuous dynamic optimization model is constructed.The management and service optimization of campus big data platform can be carried out from many aspects,including the optimization of archives information management in Colleges and Universities,wireless network layout optimization,cloud storage optimization of teaching resources,and the optimization of teaching platform service,this paper optimizes the research of campus big data platform from two aspects:1.University wireless network layout optimization.With the popularity of wireless network and the change of education mode in domestic colleges and universities,colleges and universities begin to use mobile devices to learn and build wireless network.At this stage,it has achieved comprehensive coverage within the campus.However,the demand for wireless network is gradually increasing due to the aggregation of people’s traffic in the campus,especially in the area of crowd intensive activities.In order to solve the network congestion under the condition of full coverage of wireless network,the wireless network management of colleges and universities should be optimized.At present,there are some problems in the layout management of wireless network in Colleges and Universities:first,it lacks objectivity,which is basically subjective decision-making,and it is not considered in the working and learning environment of front-line staff and students;second,there is no unified channel to collect feedback information from teachers and students,so it is difficult to improve network services.For the above problems,this paper constructs a wireless network AP optimization model,through the location information of teachers and students,school network equipment monitoring information and campus per capita bandwidth analysis of the new AP location,the AP layout state will become the base point of the next optimization,forming a dynamic,long-term optimization process.2.Teaching platform service optimization.With the change of teaching methods and the development of online teaching,the teaching resources stored in the teaching platform show explosive growth,which leads to the decrease of the access speed and storage performance of the teaching platform.In order to solve a series of problems brought by the teaching resources,this paper optimizes the service of the teaching platform.In view of the above problems,this paper proposes a teaching platform service optimization model,starting from the performance and storage.First,use Azkaban timing task scheduling task to distinguish the hot resources,put them into Redis cache and update the hot resources regularly,so as to solve the performance problems caused by the growth of teaching resources.Second,improve Azkaban timing task scheduling,clean up the cold resource data regularly and improve the performance The rollback of row cold resource data solves the storage problem.Based on the campus big data platform of central China Normal University,this paper explores the application of wireless network AP layout optimization and teaching platform service optimization,which can verify that the wireless network AP layout optimization can achieve the purpose of improving the quality of network service and improving the online experience of teachers and students.It shows that the teaching platform optimization model based on campus big data can effectively improve the access speed of the platform and achieve resource clearing Manage and roll back and improve storage utilization.