( en Inventor Colleen CLANCY Pei-Chi Yang Kevin DEMARCO Sergei NOSKOV Yibo WANG Laura L. Google Patents WO2017172825A2 - Methods and systems of predicting agent induced effects in silico Try It YourselfĪ standalone project that demonstrates these principles against an H2 database is available here.WO2017172825A2 - Methods and systems of predicting agent induced effects in silico
Public class EgressAgent extends AbstractAgent write = mandLane()Įvery Agent that has something to push then simply commands all messages to nodeUri="/egress", laneUri="write". Thus, if every message sent to the sink originates from the same lane callback, then we do not need a threadsafe connector.Īn easy way to do this is to create a singleton EgressAgent, with a single command lane whose onCommand simply relays messages to the connector: // swim/basic/EgressAgent.java Lane lifecycle callback functions execute uninterrupted in a single thread. Then, every time you reach a point within a lane callback function where you want to push to the driver, simply invoke CustomDriver.push(yourMessage), as demonstrated in the following section. impl will vary, but will use `instance` in some way We recommend having a singleton wrapper around your connector: // swim/basic/CustomDriver.java With this guarantee, performing the pushes is quite easy. If many different lane callback functions concurrently access the connector, then the connector must be threadsafe for everything to work. Since well-implemented nonblocking connectors usually have their own associated thread pool, it is imperative to instantiate as few instances of them as possible (usually just one). If it is a database, you may consider a mature ADBA implementation (though the official subset likely has everything you'll need). If your data sink is an HTTP server, this might be an AsyncHttpClient instance. Therefore, fundamental to these egress bridges is a nonblocking driver. Simple push-type logic, such as HTTP POSTs or database writes, often involve blocking calls, which will bog down not only the current Agent but also Agents scheduled for future execution by the same thread. Running Swim agents on a single machine "in parallel" only works because each agent executes in a thread pool. If the sink is another Swim server, then the egress bridge can be as simple as sending commands from the source to the sink, or updating downlinks that were instantiated in the source and link to the sink.įor non-Swim sinks, implementing a push-based egress bridge requires some care.
push) data to a different process (hereafter the sink). This high-level egress bridge design has your Swim server write (i.e. Pull-type ingress bridges are awkward in practice unless the data sink is another Swim server (in which case the implementation simply degenerates into Swim downlinks), so we will not discuss them further here.
Several egress bridge implementations are possible, but all of them can be categorized into one of two high-level models: pull-type and push-type. We hereafter call any logic that enables this flow an egress bridge for an application, as it enables egression of data from our Swim server. There are two directions of data flow: from Swim to external processes, and from external processes to Swim. Swim's built-in networking stack enables communication with other processes-which might themselves be other Swim servers.
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