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Selecting Programming Languages for the IoTBy Promotion Published Date 20 - Mar - 2017 | Last
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The Internet of Things Ecosystem
To understand which languages you canapply to your IoT projects, you must firstunderstand the IoT ecosystem. Thisknowledge is important because theprocessor architectures and resourcesavailable to your software or firmware willdiffer greatly at each level. Let’s start by defining a simple taxonomy of
DIGIT APPS SELECTING PROGRAMMING LANGUAGES FOR THE IOT
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IoT devices for which you’re developingsoftware (see Figure 1).
Figure 1. Taxonomy for Internet of Thingsdevices
At the bottom are the edge devices. Thesedevices interact with the world and representthings like wearables and other connecteddevices. The devices source and create dataand interact with the world throughactuators.
Next are the gateways. These devices can beintermediary devices that move data to othersystems for processing. The gateways canalso aggregate data from many edge-devices and provide a control path to edgedevices.
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Finally, there’s the cloud. The cloud is ascalable set of compute, network, andstorage resources that provide the ability tostore, analyze, and visualize data from edgedevices and gateways.
Examples of these levels include the Intel®Galileo board and the Intel® Curie™Compute Module for edge devices, Intel® IoTGateways for the gateway level, and theWind River* Helix* Lab Cloud for the cloudlevel.
With the IoT ecosystem divided into itslayers, let’s look at which languages you canapply at each level.
Edge Device
Edge devices, such as wearables, are typicallyconstrained-resource, embedded systemsbecause of the space and power constraintsin which they function. Devices like the Intel®Curie™ module are the size of a button, andcan be powered by a small, coin-sizedbattery (see Figure 2). Given the minimalresources of the Intel® Curie™ module, thetypical languages suitable for its use includeAssembly and C. Although C is the linguafranca of embedded firmware development,there are times when you need to squeezeas many instructions as possible into adevice. In such cases, Assembly is your bestchoice. The downside is that development
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time can be longer depending on yourexpertise with the language.
Figure 2. The Intel® Curie™ ComputeModule
Another example of an edge device is theIntel® Edison board (see Figure 3), which youcan use in the wearables space or in generalIoT products. Differing from the Intel®Curie™ module, which incorporates amicrocontroller, the Intel® Edison boardincludes a dual-core Intel® Atom™processor with considerably more computingpower (the size of an SD card). Because theIntel® Edison board runs Linux*, the Clanguage is an ideal choice here, but youcould use other languages, as well, includingPython* and Node.js*. Python* is ideal for
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quick prototyping and productiondeployment, but can lag in performancecompared to native compiled C. If you useIntel® XDK, you can also run Node.js*(JavaScript*) with Node-RED*. Node-RED*makes it easy to build and run data flows,offering a graphical approach todevelopment. Knowledge of the JavaScript*language makes this environment even morepowerful.
Figure 3. The Intel® Edison board
Gateway
At the gateway level, the compute capabilityrises greatly because gateways areresponsible for communication and analysisof data from many devices through several
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different buses. With this additionalcomputing capability comes the ability to runmore powerful languages or interpretedlanguages with greater performance.
Intel® IoT Gateways provide a variety ofdesigns that scale from a single-core Intel®Quark™ system on a chip to a quad-coreIntel® Atom™ or Intel® Core™ processor(see Figure 4). These platforms supporteither Wind River Linux* 7 or the SnappyUbuntu* Core (Linux*).
Figure 4. An Intel® IoT gateway
In addition to support for C and C++ (which isalso ideal for higher-performance devices),you can use Python*, but at greaterexecution speeds. Node.js* with JavaScript*
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is also available, which is ideal for creating orconnecting to web-services as well as tocloud services.
Cloud
When you reach the cloud, the computingcapability increases drastically, as do thelanguage choices. In the cloud, you’ll findservers enabled through power-efficient IntelAtom and Intel Core processors as well ashighest-compute-density Intel® Xeon®processors. Apps written in the cloud serve avariety of needs, and as such, the languagesyou use here can differ greatly. To processthe massive amounts of data that IoT edgedevices create, you can use big-dataframeworks like Apache Hadoop*. On top ofHadoop, query languages such as ApacheHive* enable computation over massive datasets with Structured Query Language (SQL)-like queries. Apache Pig* is also useful forexperimentation with large data sets in thePig Latin scripting language.
Data analytics and visualization are other keyapplications within the cloud that manyprogramming languages enable. A popularlanguage and environment for statisticalcomputing and visualization is the Rlanguage, which has recently grown inpopularity. The Julia language is anotheroption here. Julia is a high-performance,dynamic language designed with cloudcomputing in mind.
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You use several languages to build web-services to monetize data in the cloud,including JavaScript*, Node.js*, or server-sideand client-side Java*. Given manyframeworks and supporting languages (suchas Rails and Ruby), the languageopportunities in this space is large andgrowing.
Summary
Choosing a programming language for aproject requires consideration of the targetenvironment (including the processor) as wellas the resources available to it. Developingsoftware in the cloud opens manypossibilities, given the scale of resourcesavailable, but developing embedded firmwarefor smaller microcontrollers requires greatercontrol to minimize instruction count andmaximize execution speed and resourcemanagement.
The following list briefly summarizes thelanguages discussed in this article, andidentifies their key use models: Assembly: Developing firmware in the nativeinstruction set provides the greatest controlin resource-constrained systems such asedge-devices.
C/C++: One step above Assembly, C andC++ enable construction of resource-constrained code but with readability and
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maintainability. C’s prominence allows youto find it in every use model.Python*: An interpreted language thatsimplifies prototyping, you can also use itfor production. Python* supports amassive number of libraries and modulesso that you can get more done with lesscode. It’s useful in more powerful edgedevices, gateways, and even the cloud.JavaScript*/Node.js*: A popular languageand runtime, each enables thedevelopment of scalable networkapplications and can be applied across usemodels.Node-RED*: Developing visually withNode-RED* makes it easy to build dataflows that include sensors and actuators. Ifyou know JavaScript*, these flows can beeven more powerful. You can apply thislanguage at gateways and within morepowerful edge devices, such as those thatthe Edison board powers.HiveQL: If you’re using Hive (built onHadoop), you can use HiveQL to processmassive data sets in cloud environments.Pig: Using Pig Latin to process big dataenables quick script development andsimple experimentation of data sets withinthe cloud.R: An increasingly popular statisticalcomputing language for the processing andvisualization of data, you can apply datamining with R in cloud environments. R isalso open source.
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Julia: Another high-performance languagefor processing and visualizing data in cloudenvironments, Julia is also open source. Itwas designed with parallelism in mind andincludes key elements for distributedcomputation.Java*: A popular server-side and client-sidelanguage for the Web, making it useful inthe cloud for both web and web servicesdevelopment.
For more such intel IoT resources and toolsfrom Intel, please visit the Intel® DeveloperZone
Source:https://software.intel.com/en-us/articles/selecting-programming-languages-for-the-iot
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