DCEP is the complex event processor in PLAY. Our approach is based on declarative (logic) rules. We will bring this approach to the cloud creating a large-scale, elastic CEP service which dynamically adapts to fluctuating event frequencies.
|Main research challenges||
• Algorithms for dynamic operator placement in an elastic Event Processing Network for the cloud
|Beyond state of the art:||
• Processing events in a dynamically changing topology in the cloud
|The role in the whole platform||
Complex event processing is a technology which allows correlating basic events to complex events closely aligned with the semantics of services and processes in PLAY where the events originate. It is the role of DCEP to detect context and patterns in events which resemble situations of interest to notify users and services.
|Web applications today create a lot of events. To make sense and react to these events, generic services are scarcely available. Mashup services only provide limited capabilities of detecting and aggregating such events. Thus, in this section we propose a generic Complex Event Processing (CEP) service for the Web. This service should be available to multiple tenants and be able to deal with a high throughput of events in an elastic manner, utilizing computing resources in a cloud. This section collects challenges in the current state of the art.
The role of CEP is to detect complex events using events from various distributed sources such as federated SOAs.
The distributed Complex Event Processing engine will use virtualized computing resources to meet changing demand for event processing. Thereby, complex event-driven communication is provided for large, highly distributed and heterogeneous service systems.
Our approach to CEP is based on declarative (logic) rules. Using rules for CEP has various advantages. First, they are expressive enough and convenient to represent diverse complex event patterns. They come with a formal declarative semantics. Moreover, declarative rules are free of side-effects (e.g. confluence problem). Second, integration of query processing with event processing is easy and natural (e.g. processing of recursive queries). Third, our experience with use of logic rules in implementation of the main constructs in CEP as well as in providing extensibility of a CEP system is very positive and encouraging (e.g. number of code lines in logic programming is significantly smaller than in procedural programming). Ultimately, a logic-based event model allows for reasoning over events, their relationships, entire state, and possible contextual knowledge available for a particular domain. Reasoning about temporal knowledge (i.e., events) and static or evolving knowledge (i.e., facts, rules and ontologies) is a feature beyond of the state of the art in CEP. Taking inference capability into account, logic-based CEP provides a powerful combination of deductive capabilities and temporal features.
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|PLAY D3.1 Requirements for DCEP||2011-11-17||219.81 KB||483|
|PLAY D3.2 Distributed CEP - Specification and Prototype V1||2012-04-02||440.98 KB||357|