Expects cPacket pointers as value, and outputs the byte length for each received one. For each value, computes the sum of values received so far, divides it by the duration, and outputs the result. Removes repeated values, i. Records the count of the input values into an output scalar; functionally equivalent to last count. Records the sum of the input values into an output scalar or zero if there was none ; functionally equivalent to last sum.
Records the minimum of the input values into an output scalar or positive infinity if there was none ; functionally equivalent to last min. Records the maximum of the input values into an output scalar or negative infinity if there was none ; functionally equivalent to last max. Records the mean of the input values into an output scalar or NaN if there was none ; functionally equivalent to last mean.
Regards the input values with their timestamps as a step function sample-hold style , and records the time average of the input values into an output scalar; functionally equivalent to last timeavg. Computes basic statistics count, mean, std. Computes a histogram and basic statistics count, mean, std. Part of the class library's functionality has already been covered in the previous chapters, including discrete event simulation basics, the simple module programming model, module parameters and gates, scheduling events, sending and receiving messages, channel operation and programming model, finite state machines, dynamic module creation, signals, and more.
This chapter discusses the rest of the simulation library. Topics will include logging, random number generation, queues, topology discovery and routing support, and statistics and result collection.
This chapter also covers some of the conventions and internal mechanisms of the simulation library to allow one extending it and using it to its full potential. Otherwise, cObject is a zero-overhead class as far as memory consumption goes: it purely defines an interface but has no data members. Thus, having cObject a base class does not add anything to the size of a class if it already has at least one virtual member function. Figure: cObject is the base class for most of the simulation library The subclasses cNamedObject and cOwnedObject add data members to implement more functionality.
The following sections discuss some of the practically important functonality defined by cObject. For them, getFullName returns the name with the index in brackets, while getName only returns the name of the module or gate vector. That is, for a gate out[3] in the gate vector out[10] , getName returns "out" , and getFullName returns "out[3]". For other objects, getFullName simply returns the same string as getName. This will ensure that the vector index will also be printed if the object has one.
Actual storage for a name string and a setName method is provided by the class cNamedObject , which is also an indirect base class for most library classes. Thus, one can assign names to nearly all user-created objects. It it also recommended to do so, because a name makes an object easier to identify in graphical runtimes like Tkenv or Qtenv. By convention, the object name is the first argument to the constructor of every class, and it defaults to the empty string.
To conserve memory, several classes keep names in a shared, reference-counted name pool instead of making separate copies for each object. The runtime cost of looking up an existing string in the name pool and incrementing its reference count also compares favorably to the cost of allocation and copying. That is, "" is stored as nullptr but returned as "". If one creates a message object with either nullptr or "" as its name string, it will be stored as nullptr , and getName will return a pointer to a static "".
This name is produced by prepending the full name getFullName with the parent or owner object's getFullPath , separated by a dot. For example, if the out[3] gate in the previous example belongs to a module named classifier , which in turn is part of a network called Queueing , then the gate's getFullPath method will return "Queueing. This is especially useful in the case of message objects. The rationale is that the name string is often used for identifying the particular object instance, as opposed to being considered as part of its contents.
For many of them, there is a corresponding iterator class that one can use to loop through the objects stored in the container. This exception is then caught by the simulation environment which pops up an error dialog or displays the error message. Enabling the debug-on-errors or the debugger-attach-on-error configuration option lets you do that -- check it in section [ In order to understand a complex simulation, it is essential to know the inputs and outputs of algorithms, the information on which decisions are based, and the performed actions along with their parameters.
In general, logging facilitates understanding which module is doing what and why. The API provides efficient logging with several predefined log levels, global compile-time and runtime filters, per-component runtime filters, automatic context information, log prefixes and other useful features.
In the command-line user interface Cmdenv , the log is simply written to the standard output. In the graphical user interfaces, Tkenv and Qtenv, the main window displays the log output of all modules by default. One can also open new output windows on a per module basis, these windows automatically filter for the log messages of the selected module.
The assigned log level determines how important and how detailed a log statement is. When deciding which log level is appropriate for a particular log statement, keep in mind that they are meant to be local to components. Log levels are mainly useful because log output can be filtered based on them. It is only useful for configuration purposes, it completely disables logging. It should be used for fatal unrecoverable errors that prevent the component from further operation.
It doesn't mean that the simulation must stop immediately because in such cases the code should throw a cRuntimeError , but rather that the a component is unable to continue normal operation. For example, a special purpose recording component may be unable to continue recording due to the disk being full. For example, a MAC layer protocol component could log unsuccessful packet receptions and unsuccessful packet transmissions using this level.
For example, a MAC layer protocol component could log detected bit errors using this level. For example, a MAC layer protocol component could log successful packet receptions and successful packet transmissions using this level. These messages may help to track down various protocol-specific issues without actually looking too deep into the code.
For example, a MAC layer protocol component could log state machine updates, acknowledge timeouts and selected back-off periods using this level.
These messages may help to debug various issues when one is looking at the code. For example, a MAC layer protocol component could log updates to internal state variables, updates to complex data structures using this level. It should be used for low-level implementation-specific technical details that are mostly useful for the developers of the component. In fact, they automatically capture a number of context specific information such as the current event, current simulation time, context module, this pointer, source file and line number.
The final log lines will be automatically extended with a prefix that is created from the captured information see section [ For example, a module test may check for a specific log message in the test's output. Putting the log statement into the test category ensures that extra care is taken when someone changes the wording in the statement to match the one in the test.
Mostly because some computation has to be done between the parts. This can be achieved by omitting the new line from the log statements which are to be continued. And then subsequent log statements must use the same log level, otherwise an implicit new line would be inserted. In such cases, there's no need to write multiple log statements. This is mainly useful when printing is really complicated algorithmically e.
The following code could produce multiple log lines each having the same log prefix. The implementation fully supports conditinal compilation of log statements based on their log level. It automatically checks whether the log is recorded anywhere. It also checks global and per-component runtime log levels. The latter is efficiently cached in the components for subsequent checks. See section [ This solves conditional compilation, and also helps runtime checks by redirecting the output to a null stream.
Rarely just the computation of log statement parameters may be very expensive, and thus it must be avoided if possible. In this case, it is a good idea to make the log statement conditional on whether the output is actually being displayed or recorded anywhere. Thus, one can write code like this: if! Rather, they are produced using deterministic algorithms. Such algorithms and their implementations are called random number generators or RNGs, or sometimes pseudo random number generators or PRNGs to highlight their deterministic nature.
The algorithm's internal state is usually initialized from a smaller seed value. Starting from the same seed, RNGs always produce the same sequence of random numbers. This is a useful property and of great importance, because it makes simulation runs repeatable.
RNGs are rarely used directly, because they produce uniformly distributed random numbers. When non-uniform random numbers are needed, mathematical transformations are used to produce random numbers from RNG input that correspond to specific distributions. This is called random variate generation, and it will be covered in the next section, [7.
It is often advantageous for simulations to use random numbers from multiple RNG instances. For example, a wireless network simulation may use one RNG for generating traffic, and another RNG for simulating transmission errors in the noisy wireless channel.
Since seeds for individual RNGs can be configured independently, this arrangement allows one e. A simulation technique called variance reduction is also related to the use of different random number streams.
When assigning seeds, it is important that different RNGs and also different simulation runs use non-overlapping series of random numbers. Overlap in the generated random number sequences can introduce unwanted correlation in the simulation results. Matsumoto and T. Nishimura [ Matsumoto98 ]. MT has a period of 2 -1 , and dimensional equidistribution property is assured.
This RNG is still available and can be selected from omnetpp. This RNG is only suitable for small-scale simulation studies. As shown by Karl Entacher et al.
The [ Hellekalek98 ] paper provides a broader overview of issues associated with RNGs used for simulation, and it is well worth reading. It also contains useful links and references on the topic. This needs to be configured in omnetpp. This mechanism, based on the cRNG interface, is described in section [ For example, one candidate to include could be L'Ecuyer's CMRG [ LEcuyer02 ] which has a period of about 2 and can provide a large number of guaranteed independent streams.
However, usually model code doesn't directly work with those RNGs. Instead, there is an indirection step introduced for additional flexibility. Unable to locate element using selenium webdriver in python. Print a random row from a mysql query. Validation not working in partial view. Symfony upgrade to 3.
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