Using a Causal Vector Engine, the perception of causality can be enhanced under appropriate spatiotemporal conditions based on structural and temporal rules written into the engine. Perception of complex causal semantics, such as additive, mediated, and bidirectional causalities need to be coded so that the engine can distinguish between events that are related and those that only appear to be related but, in fact, are not.
The engine uses preponderant causal vector rate-of-change propagation to code the relationship among the events and establishes a partial order in which it validates the causality perceived between multiple occurrences. The engine plays and replays the event sequence in different temporal order to infer what could be related topological connections and compares these replays to rules preprogrammed by an analyst. Multiple low-level system events are processed by the Causal Vector Engine and compared against these rules to trigger higher-level Business Events.
It does this through a Causality Vector Engine CVE console application which displays events in real-time to business analysts.
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Where streams of events can be observed as they occur, much like a stock ticker, the CVE console app has several windows that list the same events in different contexts, so the business analysts can see what the CVE is doing with the relationships between them. The Sequential window shows events in date-timestamp order, one or more other windows in various orders as the CVE works through the list of rules and creates implied relationships between the events.
Various buttons and controls exist in the console application that enable the business analysts to create relationships between events on-the-fly and define rules that respond to these relationships. Business analysts can infuse additional defining detail through an SQL query statement attached to a rule or event context. The CVE app works much like a modern-day stock trading application that mutual funds managers use to manage risk. Most enterprise service bus ESB implementations contain a facility called " mediation ". For example, mediation flows are part of the WebSphere enterprise service bus intercept.
Mule also supports mediation flows. Mediation flows modify messages that are passed between existing services and clients that use those services. A mediation flow mediates or intervenes to provide functions, such as message logging, data transformation, and routing, typically the functions can be implemented using the Interception Design Pattern. As messages pass through the ESB, the ESB enriches the messages destined for a channel that is monitoring for a high-level business event. That is, for each message, the ESB may query a database to obtain additional information about some data entity within the message.
Or, based on IP address of the originating request by the end-user, the ESB mediation flow could lookup what country, state or county that IP address is in. These examples represent data enrichment, the concept of adding additional value to existing data, based on the intent of the high-level business event to eventually be triggered. Like any SCA component, the program accesses a mediation flow through exports that it provides, and the mediation flow forwards messages to other external services via imports.
Special kinds of imports and exports for JMS , called JMS bindings, enable developers to specify the binding configuration and write data handling code. The mediation flow consists of a series of mediation primitives that manipulate messages as they flow through the bus.
Once the developers have coded the custom binding for both export and import, they can start to focus on the mediation flow component. In the WebSphere Integration Developer assembly editor, this is done by the JMS Custom Binding Mediation Component where each operation on the flow component's interface is represented by a request and a response.
Mediation flows are entirely independent from the bindings that are used in the imports and exports. In fact, the purpose of having a conversion into an SDO DataObject instance outside of the flow implementation is because mediation flows can then be built without knowledge of the protocol and format with which messages are sent to and from the mediation module. A business-level trigger condition enables the SOA 2. Business objects model real-world entities in the architecture such as customers, accounts, loans, and travel itineraries.
When the state of one of these objects changes, and a monitoring agent notices this change is significant when compared to the list of criteria to monitor , an event is created and passed to other monitoring agents. For example, the detection of an actual business problem or opportunity could lead to increased revenue. If a customer cancels an order, extra manufacturing capacity could reduce the profitability of the production run.
A SOA 2. Automatic monitoring of events in operational business process activities as processes execute to see if any immediate action needs to be taken either inside or outside the enterprise. These monitoring agents continually test for specific business conditions and changes in business operations. If necessary, the agents alert people, make recommendations, send messages to other applications or invoke whole business processes when such conditions or changes occur.
A triggered business process should directly support revenue growth with cost containment, responsiveness to business conditions, or ability to pursue new market opportunities. Resulting business processes could also measure operational progress toward achieving goals, control operational costs by communicating just what is needed to just who needs to know, or report performance status of key processes to key decision makers. For example, you could construct a CRM event from an "abandoned shopping cart" message parsing the transaction, customer ID, and time , using other filters to extract the value of goods in the cart and tapping the correlation capabilities of the system to add causal indicators such as whether the commerce site was suffering performance problems.
Your CRM event might also include customer value or rank from the customer database. For another example, based on the types of independent service calls received, the SOA 2. Example 3: A potential use of event-driven SOA could be a virtual electricity market  where home clothes dryers can bid on the price of the electricity they use in a real-time market pricing system. On one side, consumer devices can bid for power based on how much the owner of the device were willing to pay, set ahead of time by the consumer. Further, the electricity suppliers could perform real-time market analysis to determine return-on-investment for optimizing profitability or reducing end-user cost of goods.
Event-driven SOA software could allow homeowners to customize many different types of electricity devices found within their home to a desired level of comfort or economy. The event-driven software could also automatically respond to changing electricity prices, in as little as five-minute intervals. For example, to reduce the home owner's electricity usage in peak periods when electricity is most expensive , the software could automatically lower the target temperature of the thermostat on the central heating system in winter or raise the target temperature of the thermostat on the central cooling system in summer.
The event-driven SOA software could shut off the heating element of water heaters to the pre-set response limits established by individual homeowners. For example, if the market price of electricity for a given hour exceeded the home owner's limit, the home owner could plan to go without recharging the water's hot temperature for that hour, when prices were high, and opt to delay the hot water temperature recharge to the next hour when electricity market prices might be lower. All these criteria would be managed through the home owner's personal computer with internet connection, programming the various devices around the home to consume electricity only when the management software approves of the consumption.
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