User-oriented rule management for event-based applications

Obweger, Hannes; Schiefer, Josef; Suntinger, Martin; Kepplinger, Peter; Rozsnyai, Szabolcs

doi:10.1145/2002259.2002266

Cited by 9 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another important criterion for EPS is giving data analysts the ability to customise the system according to their needs [111], which is not given sufficient emphasis, as most work on EPS does not support user-driven rule set evolution in event data analysis no matter how good the language expressiveness is. Among the very limited discussion on user-driven rule set evolution, there are two important insights: reuse of existing event patterns is of great importance for efficiency [112]; the idea of rule templates for EPS for completing rules as well as decoupled "building blocks" of rule logic is promising [113]. We agree with these insights.…”

Section: Category Technologies / Approachessupporting

confidence: 57%

Enabling user-driven rule management in event data analysis

Chen

Rabhi

2016

Inf Syst Front

View full text Add to dashboard Cite

Increasingly in the information age, overwhelming quantities of available data has brought about opportunities as well as difficulties. Data analysis is of considerable importance to finding interesting patterns, discovering useful information and making decisions accordingly. Event data has unique characteristics including temporal dependencies, high flow rate and huge volume, which makes it more difficult to analyse than other data types. Unlike data analysts working in large companies that have IT staff and expensive software infrastructure, those working in the research sector find it more difficult to efficiently manage event data analysis by themselves. User-driven rule management is a particular challenge especially when analysis rules increase in size and complexity over time. This thesis addresses these problems by proposing a new architecture called EP-RDR aimed at enabling data analysts, with no IT experience, to manage their event data analysis.EP-RDR enables complex event processing and facilitates user-driven rule set evolution according to changing requirements. The architecture leverages event processing system (EPS) technology with a rule-based method called Ripple-Down Rules (RDR). EP-RDR has two main components: an RDR component playing the role of managing the event processing logic and of supporting incremental rule insertion that enables data analysts to define and add rules by themselves, and an EPDaaS (Event Pattern Detection as a Service) component that can invoke any EPS so that data analysts are able to conduct event processing without concern about which EPS to use. To facilitate the interoperability between components in EP-RDR, this thesis also proposes an Event Data Modelling Framework (EDMF) to assist in building data models for any application of EP-RDR. EDMF consists of an Event Data Meta-Model and its associated Operational Guidelines. Any data model built based on EDMF allows event pattern types to be defined, abstracting existing event and event pattern occurrence representation formats in a consistent manner. Finally, to evaluate the proposed new method, a prototype has been implemented and applied on real-life scenarios involving financial market data pre-processing. This case study shows that the proposed method effectively satisfies requirements of event data analysis, namely feasibility and interoperability, the capability of complex event processing, and the capability of user-driven rule set evolution. viii

show abstract

Section: Category Technologies / Approachessupporting

confidence: 57%

Enabling user-driven rule management in event data analysis

Chen

Rabhi

2016

Inf Syst Front

View full text Add to dashboard Cite

show abstract

“…Third, the relevant notifications are then consumed by the governance registry that is able to use decision mechanisms such as Complex Event Processors (CEP) that apply corrective policies. Similar approaches relying on CEP are presented in several works [15,6,12], however, it is beyond the scope of this paper. We are particularly interested in detailing the development of the technical so- Third, we provide an enriched Multilevel envision for the service composition paradigm covering an increasing granularity going from services to choreographies.…”

Section: Overall Architecturementioning

confidence: 98%

Multilevel event-based monitoring framework for the petals enterprise service bus

Lesbegueries

Hamida

Salatge

et al. 2012

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems

View full text Add to dashboard Cite

In scalable and widely distributed Service-Oriented Architecture (SOA) environments, supervision is necessary to ensure services are behaving as expected and to trigger the corrective actions when needed. More specifically, when dealing with distributed and scalable Enterprise Service Bus (ESB), the control of services and their interactions must be considered at several levels and in a distributed manner. Nevertheless, in order to avoid the overhead expenses, the monitoring activity needs to be operated in a non intrusive and dynamic way. To this purpose, we propose an innovative architecture performing a multilevel service monitoring that adopts an Event-Driven Architecture (EDA), enabling a loosely coupled interaction paradigm. We realize a monitoring framework that covers coarse-grained as well as fine-grained abstractions, from choreography to orchestration and services.In this paper, we report the work resulting from our involvement in several research projects in which we study the coupling of both ESB and EDA approaches. Our experience as ESB providers shows the benefit of adopting such solutions in monitoring services and collaborations, without significant overhead. We implement and validate our framework upon our industrialized open source service bus, namely Petals ESB 1 . We envisage applying this technology to various use cases coming from Petals ESB business experience, such as administrations, civil services and corporate customers, and from research involvements.

show abstract

“…An approach for user-oriented rule management has been proposed by Obweger et. al [7,11]. They distinguish between infrastructural rules, which are defined by technical experts and are provided to business users, which finally use so-called sense-and-respond rules to create meaningful business patterns.…”

Section: Event Pattern Managementmentioning

confidence: 99%

A Methodology for Designing Events and Patterns in Fast Data Processing

Riemer

Stojanović

2013

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

View full text Add to dashboard Cite

Complex Event Processing handles processing of a large number of heterogeneous events and pattern detection over multiple event streams in real-time. Situations of interests are modeled using event patterns which describe a specific situation in an event processing language. In order to leverage the usage of event processing in everyday situations, a clear methodology for the identification and definition of events and event patterns is needed. In this paper, we propose an end-to-end methodology for designing event processing systems. This methodology integrates domain knowledge modeled during the setup phase of event processing with a high-level event pattern language which allows users to create specific business-related patterns. In addition, our methodology regards the circumstance that some patterns might have to be defined by technical experts and therefore introduces an actor model. Our approach is validated based on a real use case of a supplier of convenience stores.

show abstract

User-oriented rule management for event-based applications

Cited by 9 publications

References 15 publications

Enabling user-driven rule management in event data analysis

Enabling user-driven rule management in event data analysis

Multilevel event-based monitoring framework for the petals enterprise service bus

A Methodology for Designing Events and Patterns in Fast Data Processing

Contact Info

Product

Resources

About