Abstract: Web service technology has been utilized in the remote sensing area to increase the dynamics and scalability of remote sensing resources. However, the underlying remote sensing data of sensing services is characterized by the large-span frequent change, while the Quality of Service (QoS) values given by the service provider has the open and untrusted characteristics as well. These two aspects reduce the efficiency and accuracy of the remote service discovery, which brings forth new challenge for effective service discovery utilization in remote sensing applications. To resolve these issues, a new remote sensing service discovery mechanism based on trusted QoS clustering was proposed, in which the underlying service response time, updating frequency and the upper evaluation standards would be used to measure the QoS. Based on the QoS measurement, the updating frequency-adaptive QoS detection and updating mechanism was developed. Through the clustering, the proposed approach could increase the QoS credibility of remote sensing service. The experiment shows that the proposed approach can improve the efficiency of remote sensing service discovery and user satisfaction.

Key words: Quality of Service (QoS), trusted computing, remote sensing service, service discovery, Affinity Propagation (AP) clustering〖JP〗

摘要： Web服务技术已经在遥感领域被用于增强遥感资源的动态性和可扩展性,然而遥感服务底层的遥感数据具有大跨度频率变化的特性,服务提供商给出的服务质量(QoS)属性值也属于开放不可信，这两点都降低了遥感服务发现的效率和准确性。为此，提出一种新的基于可信QoS聚类的遥感服务发现机制，采用底层服务响应时间、更新频率和上层服务评价等标准综合衡量QoS，进而设计更新频率自适应的QoS探测和更新机制，并通过聚类方法提高了所发现遥感服务的QoS可信性。实验表明，该方法可以提高遥感服务发现的效率和用户满意度。

关键词: 服务质量, 可信计算, 遥感服务, 服务发现, 近邻传播聚类