Abstract: This paper proposed an adaptive query processing module which aimed to solve the problem that how to develop a better map plan for query to achieve users demand in limited resources of server and bandwidth on open online course system. In this paper, firstly, query expected cost matrix was set up according to the performance of resources and the cost of query tasks; secondly, the new A-MM (Adaptive Min-Min and Max-Min) algorithm that merged the merits of Min-Min and Max-Min was used for adaptive query scheduling; finally, experiments have been done and shown that the A-MM has higher efficiency and better balance capacity.

Key words: Massive Open Online Course (MOOC), adaptive query scheduling, load balance, consume load ratio, Min-Min algorithm, Max-Min algorithm

摘要： 在线课程系统中，针对如何将查询请求充分映射到有限资源上这一热点问题，设计基于系统负载平衡的自适应查询处理器。该处理器综合考虑服务器、带宽等性能指标，建立由服务资源单元和远程查询消耗单元组成的基于资源负载平衡的查询期望代价矩阵，并结合利用Min-Min和Max-Min算法的优点，提出新的自适应查询调度算法(A-MM)。实验表明A-MM有较好的执行效率和平衡负载能力。

关键词: 大规模在线课程, 自适应查询调度, 负载平衡, 负载消耗系数, Min-Min算法, Max-Min算法