A Database-Driven Algorithm for Building Top-k Service-Based Systems

The purpose of this work aims is to automatically build top-k(the number of suggested results)light weight service based systems(LitSBSs)on the basis of user-given keywords.Compared with our previous work,we use a score(oscore)to evaluate the keyword matching degree and QoS performance of a service so that we could find top-k LitSBSs with both high keyword matching degree and great QoS performance at the same time.In addition,to guarantee the quality of found top-k LitSBSs and improve the time efficiency,we redesign the database-driven algorithm(LitDB).We add the step of referential services selecting into the process of the LitDB,which could prioritize services with high quality(high keyword matching degree and great QoS performance).We design comprehensive experiments to demonstrate the great time performance of LitDB.

DS⁃CDMA下行链路多用户与扩频波形估计

针对现有基于信号子空间估计方法计算量较大的问题,提出一种基于信号子空间旋转的扩频波形估计方法。首先对观测数据的协方差矩阵进行特征分解,根据特征值分布情况估计用户数,同时获得信号子空间。进而利用信号子空间估计各用户的扩频波形,针对目前基于子空间高维搜索方法计算量大、实际应用性不强的问题,首次将Givens旋转思想应用于多用户扩频波形的估计,利用Givens旋转将多用户波形估计的高维搜索问题转化为多次一维搜索,并给出了相应Givens旋转的优化判据,实现了各用户扩频波形的快速估计。仿真实验结果表明,算法有效地降低了高维搜索方法求解的计算量,且能够在较低信噪比环境下同时估计多个用户的扩频波形。