论文标题

在边缘以信息为中心网络中有效的复杂事件处理

Efficient Complex Event Processing in Information-centric Networking at the Edge

论文作者

Luthra, Manisha, Pfannmüller, Johannes, Koldehofe, Boris, Höchst, Jonas, Sterz, Artur, Hark, Rhaban, Freisleben, Bernd

论文摘要

以信息为中心的网络(ICN)是一种新兴的Internet体系结构,提供了有希望的功能,例如网络内存和命名数据地址,以支持边缘计算范式,特别是Things Internet(Iot)应用程序。 ICN可以从复杂的事件处理(CEP)中受益,这是一个网络处理范式,用于在数据流上指定和执行有效的查询操作。但是,由于以下原因,将CEP集成到ICN中是一项具有挑战性的任务:(1)典型的ICN体系结构并不能为转发和处理连续数据流提供支持; (2)物联网应用程序通常需要较短的响应时间,并且需要强大的事件检测,这两者都很难使用现有的CEP系统来完成。 在本文中,我们介绍了一种名为Inetcep的新型网络体系结构,以作为ICN的一部分,用于有效的基于CEP的网络处理。 INETCEP通过(1)支持连续数据流的统一通信模型在ICN中启用有效的数据处理,(2)CEP的元查询语言可以在数据平面中指定数据处理操作,以及(3)查询处理算法以解析指定的操作。我们对两个物联网用例和数据集的实验结果表明,INETCEP在高工作负载下提供的响应时间最高为73μs,并且在转发事件方面比最先进的CEP系统更快地超过15倍。此外,复杂查询的传递和处理比弗林克快32倍,比基于天真的拉力参考方法快100倍以上,同时保持100%的精度。

Information-centric Networking (ICN) is an emerging Internet architecture that offers promising features, such as in-network caching and named data addressing, to support the edge computing paradigm, in particular Internet-of-Things (IoT) applications. ICN can benefit from Complex Event Processing (CEP), which is an in-network processing paradigm to specify and perform efficient query operations on data streams. However, integrating CEP into ICN is a challenging task due to the following reasons: (1) typical ICN architectures do not provide support for forwarding and processing continuous data streams; (2) IoT applications often need short response times and require robust event detection, which both are hard to accomplish using existing CEP systems. In this article, we present a novel network architecture, called INetCEP, for efficient CEP-based in-network processing as part of ICN. INetCEP enables efficient data processing in ICN by means of (1) a unified communication model that supports continuous data streams, (2) a meta query language for CEP to specify data processing operations in the data plane, and (3) query processing algorithms to resolve the specified operations. Our experimental results for two IoT use cases and datasets show that INetCEP offers very short response times of up to 73 μs under high workload and is more than 15X faster in terms of forwarding events than the state-of-the-art CEP system Flink. Furthermore, the delivery and processing of complex queries is around 32X faster than Flink and more than 100X faster than a naive pull-based reference approach, while maintaining 100% accuracy.

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