design and implementation of paas-oriented performance modeling system for web applications

按需供给是PaaS平台面临的一个核心挑战。传统以局部优化为目标的反馈控制方法难以实现全局资源供给最优,为了更合理分配资源,利用性能模型预测Web系统的资源需求就变得至关重要。随着平台服务化的发展,其部署方式由封闭环境转为开放的服务形式,为模型的构造提出了新的挑战:由于应用和平台分属不同组织,大大增加了解系统全貌的难度,所以传统手工建模方法除了建模难度大之外,更难以在开放的环境下实施;在开放和动态的环境下,用户的使用难以预期,而用户行为的改变又会极大的影响系统行为,因而也有必要使模型适应用户行为的变化。针对上述问题,给出了一种动态性能建模工具的设计与实现。该工具在Web系统中插入必要的探针收集系统运行时状态,并输出为日志。通过周期性的对这些日志进行分析,从大量数据中提取出性能模型,使其与实际用户使用情况相符。文中以TPC-W基准测试为例,验证了该系统的有效性。国家973重点基础研究发展计划基金项目(2009CB320704)|国家自然科学基金项目(61173003)|国家科技重大专项“核高基”基金项目(2011ZX03002-002-01)On-demand provision is a core challenge for PaaS platform. Traditional feedback method solves the problem of local optimization and is hard to realize global optimization of resources provision. In order to allocate resources reasonably, performa-nce model plays an important role in predicting resources demand of Web applications. However, with the development of the service platform, the way of deployment is changed from closed environment to an opened one, such as PaaS. New challenges are broughr for performance modeling of such systems. First, it is difficult to build a performance model in advance, because applications and platforms belong to different organizations. Second, in the opening and dynamic environment, the user behaviors is unexpected, which makes it is necessary to let the model adapt to the change of the mixed workload mode. To solve above problems, a dynamic performance modeling tool is designed and implemented. The tool is used to collect the running condition of Web systems at first step by inserting necessary probes into those Web systems and writing to log files. And then through periodically analyzing these log files, the tool extracts a performance model from the mass data which is in coincidence with the use condition of Web users. At last, our work is evaluated with TPC-W bench mark, whose results can demonstrate the effectiveness of our approach

基于CBERS-02卫星数据和地面测量的生物量估算及其影响因素分析

以中国科学院千烟洲生态站及其周围地区为研究区域,利用CBERS-02卫星的CCD数据和地面野外样方调查数据,探讨了千烟洲主要人工林马尾松、湿地松的植被指数NDVI和生物量之间的关系模型．和千烟洲地面生物量调查数据结果对比,表明利用CBERS-02卫星CCD的NDVI可以用于生物量估算,但NDVI和生物量模型具有一定的局限性,即这种模型依赖不同的树种．利用CBERS-02卫星高分辨率数据进行的不同空间尺度分辨率下NDVI对生物量估算的影响因素分析表明,对于植被覆盖比较大的千烟洲地区,NDVI的非线性特征对NDVI尺度扩展影响很小；但随着像元空间尺度的扩展,像元NDVI值发生了相应的变化；而由于空间尺度扩展引起的像元类型(属性)的变化,会由于生物量模型的适用性差异而使生物量估算产生比较的大误差