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

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 \system, for efficient CEP-based in-network processing as part of \ac{ICN}. \system 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 \system offers very short response times of up to $73 \mu s$ under high workload and is more than $15 \times$ 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 $32\times$ faster than Flink and more than $100\times$ faster than a naive pull-based reference approach, while maintaining $100\%$ accuracy.