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-  2018 

GWR与STARMA结合的WMS响应时间时空预测模型
Spatiotemporal-Aware Hybrid Prediction Model for Response Time of Web Map Services by Integrating GWR and STARMA

DOI: 10.13203/j.whugis20160370

Keywords: OGC WMS,响应时间,时空预测模型,STARMA,GWR,
OGC web map service
,response time,spatiotemporal prediction model,STARMA,GWR

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Abstract:

响应时间作为一项非功能性属性,是网络服务性能的重要度量指标。它直接影响了用户的服务体验,并在服务资源选择中扮演重要的角色。响应时间不仅受制于服务自身的软硬件性能,同时还受到用户访问时空分布差异性的影响,具有显著的不确定性,因此如何可靠地预测响应时间是一个难点。选取OGC WMS (web map service)为研究对象,通过全球多地分布式部署的监测系统获取服务响应时间,在分析WMS响应时间与时空因素的关联关系及其变化规律基础上,提出地理加权回归(geographical weighted regression,GWR)与时空自相关移动平均(spatial-temporal auto regressive and moving average,STARMA)相结合的WMS响应时间时空预测模型。该模型综合考虑了用户访问时空分异特征对WMS响应时间的影响,其中GWR部分描述服务响应时间的时空趋势,STARMA部分拟合时空序列局部随机扰动。通过将多个地区监测点不同时刻WMS响应时间的实测数据与模型预测值对比,验证了模型的有效性。实验表明,该模型的预测精度相比经典的平均值法AVG有较大的提升,同时较GWR模型和STARMA模型的精度有一定程度的改善

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