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.
翻译:以信息为中心的网络(ICN)是一个新兴的互联网结构,它提供了前景光明的功能,例如网络内缓存和命名的数据处理,以支持边缘计算模式,特别是TH(IoT)应用程序。ICN可以受益于复杂事件处理(CEP),这是一个网络内处理模式,可以对数据流进行具体化和高效的查询操作。然而,将CEP纳入ICN是一项具有挑战性的任务,其原因如下:(1) 典型ICN架构不支持发送和处理不断的数据流;(2) IoT应用程序往往需要较短的反应时间,需要强有力的事件探测,而这两者都很难利用现有的CEP系统完成。在文章中,我们提出了一个新的网络结构,称为系统,作为\ac{ICN}的一部分,高效的CEPEP网络内部处理(CEP)处理。由于以下原因,将CEP纳入ICN的高效数据处理是一项具有挑战性的任务:(1) 一个支持连续数据流的统一通信模式,(2) CEB的元查询语言,用于指定数据平流的数据处理业务,以及3 查询算算算算算算算方法,用以解决规定的操作,而不能用现有的CEBEBRLLLLLLLLLLLLR的交付的交付中,而不能在高时间中,而使IM的交付的交付的交付中,而使IMLLLLLLLLLLLLLL的交付的交付的交付量在两个运行中,在超过R的交付量中,在运行中,在高时段次中,在运行中,在运行中,在运行中,在运行。我们的实验结果能够显示比在两次中,在两个中,在高时中,在运行。