Friday

Summary: A Personal Experiment & A New Model for Open, Open-source, Anonymous & Secure Wireless Communication
Communication, Network, Protocol Design & Implementation Using Arduino & Raspberry Pi


Updated Nov 23, 2016

Over the course of the last few years, I have been working on a standardized, open-source communication stack that can be scaled from the biggest, most powerful devices, to tiny inexpensive devices like Arduino micro-controllers.

This looks familiar!

In the course of this time, I've made great progress in development of the core RF24 radio driver for nrf24l01+ radio modules. The overall goal of this project is independent of the radio devices, but these devices were chosen due to their relative capabilities vs cost, availability and ease of use. They are simply 2Mbps half-duplex wireless communication devices. Virtually any type of wireless devices can utilize the same theory of operation, including the mesh (RF24Mesh) style protocols.

What is it ? This system/communication stack allows nrf24l01+ radio/wireless devices to be utilized as a standard Network Interface Card (NIC) using TCP/IP & Mesh protocols. This is a summary of the experiment, system, general operation, and some of what I've learned.

Why? The programming, design and implementation of this system is part of a personal experiment I've been conducting involving the nature of wireless communication systems and protocols in relation to privacy, security, the Internet and the Internet of Things.

Theory of Operation & Design:


Consideration A: Open Networks + Anonymity + Automation


In general operation the basic principle of the communication stack is thus:
1. Each device utilizes a unique identifier while connected to a given access point.
2. This 'unique' identifier essentially represents an IP address in this implementation
3. For reasons of simplicity, this implementation also requires a 'static' identifier or IP address, but using more powerful micro-controllers and radio devices, the identifier can be assigned randomly or via DHCP
4. Devices simply attach, at any point in the network, using any available node(s) as an access point.

In a large scale model incorporating this type of design, with proper randomization of identifiers, individual devices and users are (potentially) indistinguishable from one-another initially and generally anonymous.

The next stage of course involves communication to enable the IoT/automation & allowing any capable device to connect. In this case there appear to be some options:

Option A: Leave the network open, and devices can choose to encrypt/authenticate their communications.This may require additional protective measures to prevent abuse in a large or publicly accessible system.

Option B: Assign selected devices a shared "network key" of sorts and incorporate encryption protocols into the network

Either way, it seems that wireless devices & users can inherently maintain their relative anonymity in a system that is designed a little differently.


Consideration B: Mesh Networks

The Network Layer: 
In studying the different layers involved in a capable communication stack, it seemed that many of the boundaries between layers were blurry, with many different systems 'breaking the rules' as it were. A good example of this is TCP/IP which does not strictly adhere to the OSI model.


In my design, a 'static' network architecture is used, which resembles a tree configuration. The simplicity of the RF24Network layer means that each node can handle routing of any type of information, and only needs to know which nodes it is directly connected to. 

Some of the features/functionality involving the RF24Mesh layer have been placed into the RF24Network layer directly. The reasons are mainly due to efficiency and limitations of small devices and this is under review.

Due to the limitations of the specific device used ( nrf24l01+ ) radio modules, each device is limited to 5 individual connections in the mesh, but this could be easily extended for use with more powerful radio devices.

The Mesh Layer:


The mesh layer utilizes its knowledge of the 'static' network architecture to allow individual nodes to attach themselves to the network at any given point where another node is active.

As mentioned above, each device is currently pre-assigned a unique identifier from 0-255 due to the 8-bit nature of very small & low power devices. In a large scale or commercial implementation, these identifiers can be assigned automatically & randomly, with devices then registering themselves in DNS if required, or simply acting as an anonymous client.

The fundamental benefit of a mesh style network is that nodes will automatically adjust their physical address and connection as required as they move around the network or lose connectivity. Any other nodes will provide connectivity by allowing other nodes to attach, and routing or accepting their traffic according to specifications.

Per RF24Network design, there is very little overhead for individual nodes, since they only need to keep track of which node they are connected to, and which nodes are using them as an access point.

Consideration CLimitations

There are currently a number of fundamental imitations and odd 'quirks' that have to be dealt with due to the nature of really small devices like 16Mhz AVR devices.

AVR Devices: The chosen limitations in this case include some of the smallest and least power hungry devices available to any consumer. ATTiny devices can operate as low layer nodes & relays using RF24Mesh, and slightly faster 328 based AVR devices can run an actual IP stack.

uIP TCP/IP Stack:  One of main issues with small devices involves certain limitations of the IP stack. As soon as slightly larger devices are utilized, more robust IP stacks are available that make operation faster and more reliable. uIP has provided a very interesting learning opportunity and is quite amazing given what it can do with extremely limited resources.

Radio Devices: nrf24l01+ radio modules are max 2Mbps half-duplex communication devices with a specific 5-byte addressing scheme.


Consideration D: Fully Automated Networks



Software and wireless development capabilities have come to the point of enabling fully autonomous networks that essentially manage themselves, devoid of human interaction. This goal has been partly realized or demonstrated in theory and action with the RF24Mesh layer, and could easily be built upon and implemented by large scale commercial interests.

The concept of independent networks that configure and maintain themselves may seem to some as a wild idea or a bit of a pipe dream, but we have all of the tools and capabilities within our grasp. It is simply a matter of engineering and development.

Connectivity of individual users can be managed entirely via authenticated and encrypted connections, so there is clearly no need for individual identification of users or user management beyond the application layer.

This type of system could allow communities to simply put up hardware and provide access. The system would be automated to the point that if a device fails, nearby devices send out an alert and the equipment is replaced. That is all.

Consideration E: Wireless Technology and Potential Breakthroughs



Communications technology, aka the Internet, has become ubiquitous in many ways to the daily life of millions and millions of individuals and businesses. Unfortunately, this type of connectivity has not been available to consumers in poor, rural or remote areas in a real, usable way.

Even with existing satellite technologies showing great promise towards providing quality communications capabilities to new places, it seems that additional measures will need to be taken to provide for the age of automation. This is the kind of automation that will see real-time control scenarios, with vehicles communicating among themselves, drawing in information from traffic control systems, news, weather, and countless other systems.  This is the kind of automation that will see drone based grocery and package delivery, combined with, at some point, flying vehicles and high speed transportation systems.

The implementation of automation on a massive scale is going to require something better than the kind of service we get from existing cellular networks and current technology. This is going to require a lot more than what public cellular, 5G and fiber technologies can provide. What we need moving forward is not just a standard step forward in communications technology, but a giant leap forward, while keeping in mind all the things that make the internet and technology beneficial to everybody.


General Summary:

It now seems entirely possible and practical to design and implement fully featured, autonomous. large scale, wireless network architecture that fundamentally provides anonymity and promotes privacy among its users, while providing full mesh networking capabilities and automated network management.

With the emerging nature of communications devices, potential breakthroughs in communication technology, and wireless/IoT/automation technology emerging as a major component of our future progress, it seems very important to study, understand and develop networking and communication technologies with us, the users in mind.

It also seems that wired communications systems have already become a thing of the past, with more and more devices embedding chips and features to support Wireless and WiFi protocols and interfaces. The importance of privacy and security is fundamental to the operation of any large or public communication system, and any large, public & worthwhile communication platform will incorporate these basic ideals as inherent to its operation.


http://nrf24.github.io/RF24Ethernet

http://nrf24.github.io/RF24Gateway


Saturday

New Sampling/Audio library for Arduino : AutoAnalogAudio
Easy access to the internal DAC(or PWM), ADC, Timers & DMA for sound generation

I've been playing around with the Arduino Due for a while now, and finally got to looking over the datasheet and playing around with some of the internals because of ongoing requests regarding audio functionality and advanced timer usage etc.

As a result of my dabbling, I've created a sampling library to simplify access to the onboard Analog-to-Digital (ADC), Digital-to-Analog (DAC), Timer and DMA peripherals.

It is a simplified API that allows users to create a wide range of audio or related applications in short order.

Auto Analog Audio (Automatic DAC, ADC & Timer) library

Goals:
Extremely low-latency digital audio recording, playback, communication and relaying using a simple API

Features:
  • New: Now supports AVR devices (Uno,Nano,Mega,etc)
  • Designed with low-latency radio/wireless communication in mind
  • Very simple user interface/API to Arduino DUE DAC, ADC, Timer and DMA
  • PCM/WAV Audio/Analog Data playback using Arduino Due DAC
  • PCM/WAV Audio/Analog Data recording using Arduino Due ADC
  • Onboard timers drive the DAC & ADC automatically
  • Automatic sample rate/timer adjustment based on rate of user-driven data requests/input
  • Uses DMA (Direct Memory Access) to buffer DAC & ADC data
  • ADC & DAC: 8, 10 or 12-bit sampling
  • Single channel or stereo output
  • Multi-channel ADC sampling
  • AVR devices with no DAC or DMA use pseudo DAC(PWM) & DMA(Timer + Memory Buffer)

Testing:

The results so far have been very good. Using the nrf24l01+ radio modules, I was able to stream a standard format *.wav file of high quality (48khz, 16-bit, Stereo) from a Raspberry Pi to the Arduino Due using a slightly modified version of the included Wireless Speaker example.

To put that in perspective: Data Rate = Sample Rate * Channels * BytesPerSample

Streaming over Radio (RF24):
Data Rate = 48,000 * 2 * 2 = 192.0KB/s 

Streaming from SD Card:
Data Rate = 44,100 * 2 * 1 = 88.2KB/s (maximum rate with noticeable slowdown)

Using an SD card is a bit less exciting, as the audio starts to slow down noticeably with audio of 44.1khz, 8-bit, Stereo. Unfortunately, the SD speed is currently a bit limited, since the HSMCI is not available on stock Arduino Due, and I haven't found a faster working library like sdFat for Due.

SdFat Lib:
The sdFat library works with the due, I just had to initialize it at SPI_DIV6_SPEED (10.25Mhz SPI), and it worked using a value of 5 (17mhz SPI) as well. Initial tests show the max read speeds with the stock SD library at about 113KB/s, and 182KB/s with sdFat lib. Adjusting the SdFatConfig.h file to set ARDUINO_FILE_USES_STREAM = 0 results in speeds of 204KB/s with my current card & module.

These numbers indicate that the Due can handle quite a bit of punishment, and is easily up to the task at hand. The main limitation seems to be the throughput of whatever device is providing the audio or recording it etc.

Initial testing on AVR devices seems to indicate functionality similar to my RF24Audio and TMRpcm libraries.

If using a faster device, or generating audio from tables stored in memory, it seems that the Due with the AAAudio library will most likely handle it.

Notes:

If using the RF24 library in combination with an SD card, I highly recommend using a separate SPI BUS for the radio and SD card. I experienced a number of problems with high speed transfers etc when attempting to extend the length of wires used or connect an SD card module as well.

See the SPI_UART library section of the RF24 docs to enable a secondary SPI BUS for the radio.
Due Pins - TX1: MOSI, RX1: MISO, SDA1: SCK, CS&CE: User selected



Installation: AutoAnalogAudio is available via the Arduino Library Manager


I've also included a number of examples that demonstrate usage:
Click: File -> Examples -> AutoAnalogAudio in the Arduino IDE

SDAudio Examples: Demonstrate how to play back and record WAV/PCM format audio from SD card using the AAAudio library

Wireless Examples: Demonstrate receiving and sending streams of audio data via nrf24l01+ radio modules and are easily modified to work with other radios or devices. Some matching examples and audio samples are included for Raspberry Pi.

Audio Generation Examples: Demonstrate playback of simple audio tones or synthesized audio.

ADC/Audio Capture Examples: Demonstrate how to capture data/audio streams from the ADC on one or more pins/channels.

Documentation: http://tmrh20.github.io/AutoAnalogAudio
Source Code: https://github.com/TMRh20/AutoAnalogAudio

AutoAnalogAudio Library - nRF52 Now supports Successive Approximation Analog-to-Digital Converter for Audio Input

 AutoAnalogAudio Library - nRF52 Now supports SAADC Support for Successive Approximation Analog-to-Digital Converter for Audio Input I'v...