Recently, I configured OpenWrt on a lot of devices and it's a great firmware for wireless routers. I read a lot about OpenWISP which is:
OpenWISP is a software platform designed to ease and automate the
management of networks, with a special focus on wireless networks,
mainly used in public wifi, mesh networks, community networks, and IoT
scenarios.
OpenWISP 2, launched in December 2016, is the new generation of the
software which is gradually replacing OpenWISP 1 and aims to build an
ecosystem of applications and tools that make it easy for developers
to build custom networking applications in order to bring innovation
in the network infrastructure of communities that most need it. [Source]
I think that it would play like an OpenWrt, however, I don't understand it completely.
OpenWISP is a web application composed with a collection of open source software tools, its aim is to allow the creation of customized network management solution, as well as to provide a default application which allows managing an OpenWRT based network.
Imagine it as a scriptable linux/python/django and web based system through which you can manage a fleet of OpenWRT devices.
Related
I need to perform some machine learning tasks using a Tensor Flow based Neuronal network architecture (PointNet https://github.com/charlesq34/pointnet). I would like to use cloud infrastructure to do this, because I do not have the physical resources needed. The demands of the customer are, that they would like to get the whole set up machine I used for the training afterward and not only the final model. This is because they are researchers and would like to use the machine themselves, play around and understand what I did but they do not want to do the setup/installation work on their own. Unfortunately they can not provide a (physical or virtual) machine themselves right now.
The question is: Is it possible/reasonable to set up a machine on a cloud infrastructure provider like google cloud or AWS, install the needed software (which uses Nvidia Cuda) and export this machine after a while when suitable hardware is available, import it to a virtualisation tool (like Virtual Box) and continue the usage on ones own system? Will the installed GPU/Cuda-related software like TensorFlow etc. still work?
I guess it's possible, but it will be needed to configure the specific hardware to make it work on the local environment.
For Google Cloud Platform,
the introduction to Deep Learning Containers, will you allow to create portable environments.
Deep Learning Containers are a set of Docker containers with key data science frameworks, libraries, and tools pre-installed. These containers provide you with performance-optimized, consistent environments that can help you prototype and implement workflows quickly. Learn more.
In addition, please check Running Instances with GPU accelerators
Google provides a seamless experience for users to run their GPU workloads within Docker containers on Container-Optimized OS VM instances so that users can benefit from other Container-Optimized OS features such as security and reliability as well.
To configure Docker with Virtualbox, please check this external blog.
MEAN stack and IOT are the current trending hot topics. Can these two be used together? If yes then in what way?
How can these technologies be used together?
Sweta.
By saying MEAN.js you are including things that are not strictly in the IoT terrain. Angular for example has little to do with anything.
On the web front end you need to implement a javascript library like Paho.js that will use the MQTT protocol to connect to a broker and start aggregating messages from connected devices.
Express has little to do as well as you are not exposing a Restful interface but connecting low level through a broker. A good solution in Node.js is Mosca.
Mongo is good for dumping data from devices.
I have written a tutorial using Node.js and iOS so have a look and you might find it interesting.
Mean stack is the combination of the frontent web frameworks like angularjs,emberjs,knockoutjs,backbonejs , javascript's backend server called nodejs and using the mongodb at top. so using these frameworks and library will make a mean stack developer.
IoT pronounced as Internet of things. iot is recently used for connected electronics devices .basically it is a form of running your program inside the electronic chip and mostly trying to connect the devices.making control on devices using the programmed chip. there are separate IDE's are avaialble for developing and testing the programme on embeded chip.
you can use angularjs as a frontend(making your GUI) for your IoT'S application.
Yes, you can.
As a fact is has been done before. And in other frontend frameworks too. Here there is an example for home automation.
You can find even a yeoman generator for such projects here.
[Disclaimer: I work here] Netbeast started managing devices and creating a system of plugins on top
of a MEAN app and RESTful communications. (Now we use a MERN
stack, with react and MQTT over websockets to control networks and
update values in real time.)
To mention other places where you can find examples of current projects using MEAN to run IoT networks I encourage you to join angular, arduino and raspberry communities, as well as taking a tour over producthunt.com, hackster.io and other maker sites such as the previously mentioned Netbeast forum.
Yes you can make an IoT platform with the MEAN stack. Typically the sensors are low cost sensors and are constantly transmitting small amounts of data in MQTT or TCP protocols. With Node.js you can write, servers for such applications very easily.
Mongo is useful if you have unstructured data, which could happen if you work with multiple sensors. If you don't need unstructured data structures, SQL is sufficient.
All the data that you get from devices, finally needs to be consumed via applications. Express and Angular are great platforms to manage web applications.
You can read a little more about IoT platforms in MEAN at http://blog.yatis.io/scalable-iot-platform-mean-stack/
I am a new commer in SOC, I have a question about two systems,
OpenWRT and μTenux.
It seems both solutions can work, but what is the difference between each?
When should we use OpenWRT for the basis of a new application? When should we use μTenux?
I want to write a SOC application, which can make socket connection to website and fetch a config file. Which system should I choose?
OpenWrt is a Linux based OS tailored towards router software, i.e. it has web front-end for configuring various network parameters. It is more suitable for server side.
μTenux seems to be bare metal real-time OS, i.e. not Linux based. It is capable of fetching a config file via web.
If you just want to write a client application I would recommend Buildroot.
I want to know what is the difference between these two implementations of neo4j. Of-course names of both techniques is self-explanatory,but still what are the main differences?
What factors should be considered in deciding which technique to use in the project?
Pros and cons.
P.S. Sorry if it is a repeat question but I searched and was not able to find any ques which answers my question.
Because the standalone server is built on the embedded server, the general rule of thumb is that the embedded server is more capable and has (obviously) lower latency. Either can operate in High-Availability mode, allow monitoring, and even accept connections from the neo4j-shell. With the server though, you get more functionality out-of-the-box, like remoting, basic visualization, monitoring interface, etc.
The differences are otherwise the practical ones you'd imagine. Choosing a deployment approach is influenced by two things:
Language - embedded mode requires that you're implementing your application with a JVM compatible language. The server supports any language/framework that can send HTTP requests.
Hardware - sharing physical resources between your application and Neo4j can be demanding. Scaling may argue for a dedicated machine to split out the persistence layer. The server obviously has a remote API to support segmenting your application.
It's otherwise difficult to give guidance without a specific usage scenario. Deploying into an existing Service Oriented Architecture? Probably server. Running on an copier machine? Go embedded. From scratch web application? What's the rest of your stack?
I am currently learning Erlang
Can SO users give interesting examples of any of their Erlang application deployments?
I want to gain some insight into common Erlang uses past telecomms, and any problems or unexpected benefits Erlang brought during development/deployment.
I hope this will give some broader context and whet the whistle for myself and anyone else jumping into Erlang!
Thanks in advance!
Who uses Erlang for product development:
Bluetail/Alteon/Nortel (distributed,
fault tolerant email system, SSL
accelerator)
Cellpoint (Location-based Mobile
Services)
Corelatus (SS7 monitoring).
dqdp.net (in Latvian) (Web Services).
Facebook (Facebook chat backend)
Finnish Meteorological Institute
(Data acquisition and real-time
monitoring)
IDT corp. (Real-time least-cost
routing expert systems)
Klarna (Electronic payment systems)
Mobilearts (GSM and UMTS services)
Netkit Solutions (Network Equipment
Monitoring and Operations Support
Systems)
Process-one (Jabber Messaging)
Schlund + Partner (Messaging and
Interactive Voice Response services)
Quviq (Software Test Tool)
RabbitMQ (AMQP Enterprise Messaging)
T-Mobile (previously one2one)
(advanced call control services)
Telia (a telecomms operator)
Vail Systems (Interactive Voice
Response systems)
Wavenet (SS7 and IVR applications)
Our first application was a web/sms social network and I wrote a long paper on the subject which can be read here.
We've built a web app based on an Erlang backend.
Erlang is in charge of the business logic, the security and data store.
The browser communicates exclusively through JSON services with it and do the rendering.
It will be in beta soon, and to give you an idea of the app there is a video here
There are as well some resources here and here about what we learned along the way.
Get to know the the release tools erlang/OTP already provides.
Erlang bootscripts are wonderful for ensuring that all the running applications needed are present and of the correct version. Working within the OTP framework for releases will be much easier than trying to invent your own. Erlang has lots of tools for making sure deployments can be done both live and without breaking running services. The language and runtime are designed for this so they've done a lot of the heavy lifting for you. I've found the tools useful even for small "non-enterprise" apps and deployments.
Of course there's always applications like wings3D which is for 3D modelling. It's not exactly a "deployment", because these sorts of programs are used anywhere from individuals to teams of artists in their pipeline. There are other projects for things like simulation, but I'm not sure how many companies are publicly stating that they use Erlang. As for me, I'm planning to adopt it for my company for industrial automation.