Related papers: On Load Shedding in Complex Event Processing
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)…
In this paper, we present an approach to Complex Event Processing (CEP) that is based on DeepProbLog. This approach has the following objectives: (i) allowing the use of subsymbolic data as an input, (ii) retaining the flexibility and…
Internet of Things (IoT) domains generate large volumes of high velocity event streams from sensors, which need to be analyzed with low latency to drive decisions. Complex Event Processing (CEP) is a Big Data technique to enable such…
Training a model to detect patterns of interrelated events that form situations of interest can be a complex problem: such situations tend to be uncommon, and only sparse data is available. We propose a hybrid neuro-symbolic architecture…
Complex Event Processing (CEP) is a powerful paradigm for scalable data management that is employed in many real-world scenarios such as detecting credit card fraud in banks. The so-called complex events are expressed using a specification…
Detecting complex patterns in large volumes of event logs has diverse applications in various domains, such as business processes and fraud detection. Existing systems like ELK are commonly used to tackle this challenge, but their…
This work studies Complex Event Recognition (CER) under time constraints regarding its query language, computational models, and streaming evaluation algorithms. We start by introducing an extension of Complex Event Logic (CEL), called…
Complex event processing (CEP) systems continuously evaluate large workloads of pattern queries under tight time constraints. Event trend aggregation queries with Kleene patterns are commonly used to retrieve summarized insights about the…
Complex Event Processing (CEP) is a set of methods that allow efficient knowledge extraction from massive data streams using complex and highly descriptive patterns. Numerous applications, such as online finance, healthcare monitoring and…
Event processing will play an increasingly important role in constructing enterprise applications that can immediately react to business critical events. Various technologies have been proposed in recent years, such as event processing,…
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine…
The exponential expansion of real-time data streams across multiple domains needs the development of effective event detection, correlation, and decision-making systems. However, classic Complex Event Processing (CEP) systems struggle with…
In Complex Event Processing, handling out-of-order, late, and duplicate events is critical for real-time analytics, especially on resource-constrained devices that process heterogeneous data from multiple sources. We present LimeCEP, a…
Under several emerging application scenarios, such as in smart cities, operational monitoring of large infrastructure, wearable assistance, and Internet of Things, continuous data streams must be processed under very short delays. Several…
Emerging network architectures like Information-centric Networking (ICN) offer simplicity in the data plane by addressing named data. Such flexibility opens up the possibility to move data processing inside network elements for…
Complex Event Processing (CEP) is one technique used to the handling data flows. It allows pre-establishing conditions through rules and firing events when certain patterns are found in the data flows. Because the rules for defining such…
We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a pre-specified number of line outage that leads to the maximum…
Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to process structured data stream. Video streams are…
Distributed Stream Processing (DSP) systems enable processing large streams of continuous data to produce results in near to real time. They are an essential part of many data-intensive applications and analytics platforms. The rate at…
Distributed Complex Event Processing (DCEP) is a paradigm to infer the occurrence of complex situations in the surrounding world from basic events like sensor readings. In doing so, DCEP operators detect event patterns on their incoming…