Event-driven architecture

The first logical layer is the event generator, which senses a fact and represents that fact as an event message. As an example, an event generator could be an email client, an E-commerce system, a monitoring agent or some type of physical sensor.

Converting the data collected from such a diverse set of data sources to a single standardized form of data for evaluation is a significant task in the design and implementation of this first logical layer.[6] However, considering that an event is a strongly declarative frame, any informational operations can be easily applied, thus eliminating the need for a high level of standardization.

This is the second logical layer. An event channel is a mechanism of propagating the information collected from an event generator to the event engine[6] or sink. This could be a TCP/IP connection, or any type of an input file (flat, XML format, e-mail, etc.). Several event channels can be opened at the same time. Usually, because the event processing engine has to process them in near real time, the event channels will be read asynchronously. The events are stored in a queue, waiting to be processed later by the event processing engine.

The event processing engine is the logical layer responsible for identifying an event, and then selecting and executing the appropriate reaction. It can also trigger a number of assertions. For example, if the event that comes into the event processing engine is a product ID low in stock, this may trigger reactions such as “Order product ID” and “Notify personnel”.[6]

This is the logical layer where the consequences of the event are shown. This can be done in many different ways and forms; e.g., an email is sent to someone and an application may display some kind of warning on the screen.[6] Depending on the level of automation provided by the sink (event processing engine) the downstream activity might not be required.

Simple event processing concerns events that are directly related to specific, measurable changes of condition. In simple event processing, a notable event happens which initiates downstream action(s). Simple event processing is commonly used to drive the real-time flow of work, thereby reducing lag time and cost.[6]

For example, simple events can be created by a sensor detecting changes in tire pressures or ambient temperature. The car's tire incorrect pressure will generate a simple event from the sensor that will trigger a yellow light advising the driver about the state of a tire.

In event stream processing (ESP), both ordinary and notable events happen. Ordinary events (orders, RFID transmissions) are screened for notability and streamed to information subscribers. Event stream processing is commonly used to drive the real-time flow of information in and around the enterprise, which enables in-time decision making.[6]

Complex event processing (CEP) allows patterns of simple and ordinary events to be considered to infer that a complex event has occurred. Complex event processing evaluates a confluence of events and then takes action. The events (notable or ordinary) may cross event types and occur over a long period of time. The event correlation may be causal, temporal, or spatial. CEP requires the employment of sophisticated event interpreters, event pattern definition and matching, and correlation techniques. CEP is commonly used to detect and respond to business anomalies, threats, and opportunities.[6]

Online event processing (OLEP) uses asynchronous distributed event-logs to process complex events and manage persistent data.[7] OLEP allows to reliably compose related events of a complex scenario across heterogeneous systems. It therewith enables very flexible distribution patterns with high scalability and offers strong consistency. However, it cannot guarantee an upper bound to the processing time.

Event driven architectures have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-architectures are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values. The high degree of semantic heterogeneity of events in large and open deployments such as smart cities and the sensor web makes it difficult to develop and maintain event-based systems. In order to address semantic coupling within event-based systems the use of approximate semantic matching of events is an active area of research.[8]

The Java Swing API is based on an event driven architecture. This works particularly well with the motivation behind Swing to provide user interface related components and functionality. The API uses a nomenclature convention (e.g. "ActionListener" and "ActionEvent") to relate and organize event concerns. A class which needs to be aware of a particular event simply implements the appropriate listener, overrides the inherited methods, and is then added to the object that fires the event. A very simple example could be:

public class FooPanel extends JPanel implements ActionListener {
    public FooPanel() {
        super();

        JButton btn = new JButton("Click Me!");
        btn.addActionListener(this);

        this.add(btn);
    }

    @Override
    public void actionPerformed(ActionEvent ae) {
        System.out.println("Button has been clicked!");
    }
}

Alternatively, another implementation choice is to add the listener to the object as an anonymous class. Below is an example.

public class FooPanel extends JPanel {
    public FooPanel() {
        super();

        JButton btn = new JButton("Click Me!");
        btn.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent ae) {
                System.out.println("Button has been clicked!");
            }
        });
        this.add(btn);
    }
}

(() => {
  'use strict';

  class EventEmitter {
    constructor() {
      this.events = new Map();
    }

    on(event, listener) {
      if (typeof listener !== 'function') {
        throw new TypeError('The listener must be a function');
      }
      let listeners = this.events.get(event);
      if (!listeners) {
        listeners = new Set();
        this.events.set(event, listeners); 
      }
      listeners.add(listener);
      return this;
    }

    off(event, listener) {
      if (!arguments.length) {
        this.events.clear();
      } else if (arguments.length === 1) {
        this.events.delete(event);
      } else {
        const listeners = this.events.get(event);
        if (listeners) {
          listeners.delete(listener);
        }
      }
      return this;
    }

    emit(event, ...args) {
      const listeners = this.events.get(event);
      if (listeners) {
        for (let listener of listeners) {
          listener.apply(this, args);
        }
      }
      return this;
    }
  }

  this.EventEmitter = EventEmitter;
})();

Usage:

const events = new EventEmitter();
events.on('foo', () => { console.log('foo'); });
events.emit('foo'); // Prints "foo"
events.off('foo');
events.emit('foo'); // Nothing will happen