1 research outputs found
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 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 {\mu}s 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