FAIR：一种基于模糊聚合的实时的无线传感器网络网内恢复算法
FAIR: Fuzzy-based Aggregation providing In-network Resilience for real-time Wireless Sensor Networks
摘要：
本文介绍了FAIR，一个新的框架，基于模糊的聚合提供在网络弹性的无线传感器网络。FAIR解决了恶意聚合器节点操纵数据的可能性。它基于WSN响应的信任级别提供数据完整性，并且它容忍链路或节点故障。与现有的解决方案相比，它提供了一个通用的聚合模型，并使查询者可以看到信任级别。我们将所提出的方法分类为补充协议，以确保对传感器叶节点提供错误数据的弹性。由于我们灵活的弹性框架和模糊推理方案的使用，我们在很短的设计周期内取得了可喜的成果。
英文摘要：
This work introduces FAIR, a novel framework for Fuzzy-based Aggregation providing In-network Resilience for Wireless Sensor Networks. FAIR addresses the possibility of malicious aggregator nodes manipulating data. It provides data-integrity based on a trust level of the WSN response and it tolerates link or node failures. Compared to available solutions, it offers a general aggregation model and makes the trust level visible to the querier. We classify the proposed approach as complementary to protocols ensuring resilience against sensor leaf nodes providing faulty data. Thanks to our flexible resilient framework and due to the use of Fuzzy Inference Schemes, we achieve promising results within a short design cycle.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
