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performed in this component. We now describe the compilation and software synthesis process in more detail.
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4.4.1 Translating task annotations
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The output of the compilation process is (i) a set of config files for each node in the network, (ii) customized constructor for the AtagManager,and (iii) the network topology file in the specific format required by the NetworkArchitecture module to initialize itself. Figure 4.6 is an excerpt of the GME model interpreter that interprets the task annotations in the context of the target network and generates config files for each node of the network. In this code listing, only the task annotations oneon-node-ZD:nand nodes-per-insfunce:I are being parsed. This simple code listing is from an early version of the ATaG compiler designed to demonstrate architecture-independentprogramming for a specific case study. The DART runtime and the compiler are being continually extended to parse an increasing set of task placement annotations, and the latest code will be available through the ATaG website. Also, the language in which the model interpreter is written is (naturally) independent of the language of implementation of DART. Currently, the code generation for DART is also performed through a model interpreter written in the same language (Java). Other language options such as C++ are also available for the model interpreter. Future compilers and code generators for ATaG might not be written in Java.
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Software synthesis is performed through model interpreters in the GME environment. Model interpreters are software components that can access the information entered graphically by the user by using an API provided by the GME toolsuite. The building blocks-such as Atom, Model, Reference, and Connection-provided by the GME metamodeling environment do not have associated domain-specific semantics. It can also be argued that the building blocks-such as ATaGBehaviorR, Deployment, SensorNode, Task, and Data-provided by the domain-specific modeling environment also do not have any inherent semantics except in the mind of the programmer. It is the model interpreters written for a particular modeling paradigm that encapsulate the semantics of the domain by suitably interpreting the model components and parameters to accomplish the desired domain-specific objective.
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/ / Config file generation in the GME model interpreter public void CenerateConf igFiles 0 c configstrings = new String[ntopo.nnodesl; / / Look at all task annotations and assign them to the / / suitable nodes; parse only two types for now for (int i-0; i<atagInfo.numTasksO; i++) i TaskInfo t = atagInfo.taskInfo(i); t. instType 0 ; String instType int instparam t. instparam0 ; if ((instType.toUpperCaseO.equals("NODESuPER~INSTANCEn)) k k (instparam 1)) for (int j-0; j < ntopo.nnodes; j++) { t . assign( j ; configStrings[jl +- t . i d 0 +
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t.assign(instParam); configstrings [instParaml +- t. i d 0 +
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/ / generate instructions for data routing for (int i=O; i<atagInfo.numDataO; i++) I DataInfo d = atagInfo.dataInfo(i);
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/ / determine where the producer tasks for this data are mapped for (int j = O ; j<outChannels.length; j++) I TaskInfo producer = atagInfo.taskInfo(outChannels[j].taskO); producerMap = producer. assignment 0 ;
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/ / determine placement of consumer tasks if (inChannels.length == 0) continue ; for (int j=O; j<inChannels.length; j++) if ((inChannels[jl. interest 0 . toUpperCase0). equals("ALL,NODES"))
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TaskInfo consumer = atagInfo.taskInfo(inChanne1s [jl . task()) int [I destinations = consumer.assignment 0 ; for (int k - 0 ; k<destinations.length; k++) consumerMap.add(new Integer(destinations[k]));
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/ / generate -senddata for config file
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Generating config files for each node of the network.
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In our case, the objectives of model interpretation are:
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1. To allow the application developer to visualize the network deployment
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in two dimensions and also inspect node connectivity and sensing coverage. This facility allows the application developer to quickly create
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