Complex Event Processing (CEP)

Event-driven information systems demand a systematic and automatic processing of events. Complex Event Processing (CEP) encompasses methods, techniques, and tools for processing events while they occur, i.e., in a continuous and timely fashion. CEP derives valuable higher-level knowledge from lower-level events; this knowledge takes the form of so called complex events, that is, situations that can only be recognized as a combination of several events. 1 Application Areas Service Oriented Architecture (SOA), Event-Driven Architecture (EDA), cost-reductions in sensor technology and the monitoring of IT systems due to legal, contractual, or operational concerns have lead to a significantly increased generation of events in computer systems in recent years. This development is accompanied by a demand to manage and process these events in an automatic, systematic, and timely fashion. Important application areas for Complex Event Processing (CEP) are the following

A model-driven approach for facilitating user-friendly design of complex event patterns

Complex Event Processing (CEP) is an emerging technology which allows us to efficiently process and correlate huge amounts of data in order to discover relevant or critical situations of interest (complex events) for a specific domain. This technology requires domain experts to define complex event patterns, where the conditions to be detected are specified by means of event processing languages. However, these experts face the handicap of defining such patterns with editors which are not user-friendly enough. To solve this problem, a model-driven approach for facilitating user-friendly design of complex event patterns is proposed and developed in this paper. Besides, the proposal has been applied to different domains and several event processing languages have been compared. As a result, we can affirm that the presented approach is independent both of the domain where CEP technology has to be applied to and of the concrete event processing language required for defining event patterns

Grid-Brick Event Processing Framework in GEPS

Experiments like ATLAS at LHC involve a scale of computing and data management that greatly exceeds the capability of existing systems, making it necessary to resort to Grid-based Parallel Event Processing Systems (GEPS). Traditional Grid systems concentrate the data in central data servers which have to be accessed by many nodes each time an analysis or processing job starts. These systems require very powerful central data servers and make little use of the distributed disk space that is available in commodity computers. The Grid-Brick system, which is described in this paper, follows a different approach. The data storage is split among all grid nodes having each one a piece of the whole information. Users submit queries and the system will distribute the tasks through all the nodes and retrieve the result, merging them together in the Job Submit Server. The main advantage of using this system is the huge scalability it provides, while its biggest disadvantage appears in the case of failure of one of the nodes. A workaround for this problem involves data replication or backup.Comment: 6 pages; document for CHEP'03 conferenc

P4CEP: Towards In-Network Complex Event Processing

In-network computing using programmable networking hardware is a strong trend in networking that promises to reduce latency and consumption of server resources through offloading to network elements (programmable switches and smart NICs). In particular, the data plane programming language P4 together with powerful P4 networking hardware has spawned projects offloading services into the network, e.g., consensus services or caching services. In this paper, we present a novel case for in-network computing, namely, Complex Event Processing (CEP). CEP processes streams of basic events, e.g., stemming from networked sensors, into meaningful complex events. Traditionally, CEP processing has been performed on servers or overlay networks. However, we argue in this paper that CEP is a good candidate for in-network computing along the communication path avoiding detouring streams to distant servers to minimize communication latency while also exploiting processing capabilities of novel networking hardware. We show that it is feasible to express CEP operations in P4 and also present a tool to compile CEP operations, formulated in our P4CEP rule specification language, to P4 code. Moreover, we identify challenges and problems that we have encountered to show future research directions for implementing full-fledged in-network CEP systems.Comment: 6 pages. Author's versio

Technology Policy, Gender, and Cyberspace

Event based sampling occurs when the time instants are measured everytime the amplitude passes certain pre-defined levels. This is in contrast with classical signal processing where the amplitude is measured at regular time intervals. The signal processing problem is to separate the signal component from noise in both amplitude and time domains. Event based sampling occurs in a variety of applications. The purpose here is to explain the new types of signal processing problems that occur, and identify the need for processing in both the time and event domains. We focus on rotating axles, where amplitude disturbances are caused by vibrations and time disturbances from measurement equipment. As one application, we examine tire pressure monitoring in cars where suppression of time disturbance is of utmost importance

Event Processing through naming: Investigating event focus in two people with aphasia

Some people with aphasia may have trouble with verbs because of fundamental difficulties in processing situations in a way that maps readily onto language. This paper describes a novel assessment, the Order of Naming Test, that explores the conceptual processing of events through the order in which people name the entities involved. The performance of non-brain damaged control participants is described. The responses of two people with non-fluent aphasia are then discussed. Both 'Helen' and 'Ron' showed significant difficulty with verbs and sentences. Ron also had trouble on a range of tasks tapping aspects of event processing, despite intact non-verbal cognition. While Helen's performance on the Order of Naming Test was very similar to the controls, Ron's differed in a number of respects, suggesting that he was less focused on the main participant entities. However, certain aspects of his response pointed at covert event processing abilities that might be fruitfully exploited in therapy