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Low power mesh networking for small sensor grids

Tiny MQTT-interoperable broadcast mesh networking with simple radios

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This project is a low-resource mesh networking stack and mote with battery-powered routers based on state synchronization. The target is for the stack to use less than 2kb SRAM. Nodes use low power listening and an adaptive gossip protocol to synchronize key/values pairs with each other without relying on explicit routing or per-node addressing. For example, a light might transmit (/lamp, {"state":"on"}) to the mesh. Write (/lamp, {"state":"off"}) to the mesh, and the lamp application will notice. The powerful but simple state synchronization primitive allows you to update the state of the mesh to update the world, and update the state of the world to express the same on the mesh. Trivially bridged to a private MQTT server and managed with off-the-shelf MQTT applications.
The prototype mote hardware is also a talking clock with ADPCM-compressed audio. It uses the STM32F051, accepts battery or USB power, and has a nRF24 socket.

Ah, the nRF24L01+. The radio of broken dreams. Cheap. Enticing. Limited. 32-byte MTU and only able to listen for 6 addresses. Now what?

This radio has a native protocol that is good for a single powered listener and up to several battery-powered transmitters, but if you want to do anything more complicated (say, a peer-to-peer network instead of a star topology) you're on your own.

How can we do something more interesting within the limitations of this radio?

The solution I am pursuing is called rebroadcast mesh networking, inspired by some code designed to work over BLE on the newer nRF51 processor https://github.com/NordicSemiconductor/nRF51-ble-bcast-mesh/ . Their code includes an implementation of the trickle algorithm. Listen. Broadcast your message. If you hear your message being broadcast from another mote, quiet down.

In this way all the radios in an area synchronize their state using a density-aware number of broadcasts with no routing tables or addressing.

The original code uses integer keys. It has an instance of the trickle algorithm for each key, controlling how often each is rebroadcast. My innovation is to use string keys for ease of use and better MQTT interoperability, and to suggest, but not require, JSON values. This mesh will also include code to forget older values when a mote's memory is full, to prevent the mesh from becoming too clogged to receive new data.

For example, the message '/rgb,[255,128,192]' is only 18 bytes. A mote's application code could get this message, parse it with a streaming JSON parser, and blink. A door sensor would only have to say 0, or 1 for closed, open. Plenty of room for all the snail mail notifiers we can afford.

And what about the memory capacity of the entire network? It's true that the network will be very inefficient if it is currently retransmitting more individual keys than the individual motes can hold. Imagine I'm using only 1k of memory and I'm using 64 bytes to store my 32-byte packets, including the overhead. That's 1024/64 = 16 keys.

There's some anxiety there; do we need a lot more complexity to build a more scalable network? No. Relax. These controllers run at 48 megahertz. We should be playing Doom on them, but instead we have plenty of cycles to parse and deal with strings. And this mesh network is for my house. I don't think I can afford to buy and build enough nodes to saturate this network even after my coffee maker, dishwasher, mailbox, and alarm clock are online. And the required bandwidth (1 packet per day, for the mailbox) is also extremely low.

These radios use about the same 10mA when transmitting or when just listening. That is too much to allow battery powered routers. For that we need to implement low-power listening. Low powered listening works by putting the radios into receive mode for only an instant at a time, and by making sure a (broadcast) transmission can be heard at that time. For example, to listen, we could wake our radios for 2 milliseconds eight times a second. To be heard we have to repeat the same packet every 1 millisecond during the entire 1/8th of a second. Transmit uses a lot more power than receive, but it's OK, because our sleepy little mesh network will wait up to a minute or two to retransmit values that have not recently changed.

The finished software will be able to be used in a single microcontroller for the motes, without an OS, or as a separate serial to RF module outputting and accepting mesh events on the serial port. The gateway will connect one of the motes in serial mode to a Raspberry Pi to connect the mesh to the internet.

  • 1 × STM32F051CxT6 Microprocessors, Microcontrollers, DSPs / Microcontrollers (MCUs)
  • 1 × nRF24L01+ Radio Module
  • 1 × PAM8301 Audio ICs / Audio Amplifiers
  • 1 × CM200C-32.768KDZB-UT Frequency Control / Crystals
  • 1 × MCP1700T-3302E/MB Power Management ICs / Linear Voltage Regulators and LDOs

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  • The Beginnings of an API

    Daniel06/10/2017 at 14:26 0 comments

    The core of this project, the inelegant C++ as mentioned, is a heap priority queue linked with a sorted list of key-values and trickle algorithm instances. The key-value pairs point back to the corresponding position in the heap, so that once you have used binary search to find the key you can update its priority without having to do a linear search through the heap. It is easy to have either a heap or a sorted list, but a bit fiddly to link the two together. You must make sure that every time you update one data structure you also update the other.

    The reason these data structures are useful is because every time you receive a packet, you must look it up in the list, and every time the clock ticks, you must check to see which key has the lowest priority. With a heap the most common operation is O(1), just heap_array[0].get_priority().

    All of this will be invisible to the implementor. The API will be, just ask the radio if it got a packet, feed the packet to the mesh stack along with the current time (number of clock ticks since start), and ask the mesh stack if there is anything to transmit.

  • Whither, elegant C++?

    Daniel06/10/2017 at 03:57 0 comments

    This project is written in embedded C++11, using prepackaged algorithms to build an efficient key/value store with a pleasingly small amount of code. Frustratingly I know how to write working C++ but I don't know how to make it beautiful, with brute force stacking of pointers, parens and references everywhere to coax the necessary type out of each expression, until the compiler is happy.

    auto element = reinterpret_cast<Contained *>(malloc(packet->len));
    trickle_timer_reset(&(element->trickle), time_now);
    memcpy(&(element->payload), packet, packet->len);
    consistent(&((*existing)->payload), packet);

    My point of comparison is the stm32plus library https://github.com/andysworkshop/stm32plus, mostly templates, which makes the stm32 much easier to program. Sure, you may have to stare at it for an hour to figure out how the recursive variadic template inherits from itself but it is written with a purpose and clarity that I have yet to find in my own C++.

    I usually program in Python but I love the completely different challenge of programming for these tiny microcontrollers where every byte matters.

  • State Machine to Implement MAC

    Daniel06/08/2017 at 00:48 0 comments

    I've added some code to work on the MAC (media access control) protocol, linked from the project page. The purpose of the MAC is to keep track of when the radio should listen or transmit. The implementation is a very simple state machine that takes a single tick(time) event and transitions between states for idle, tx, and rx. We send commands to the radio when entering and leaving states, and can easily avoid trying to transmit when we should be receiving and vice versa.

    The state machine is based on this popular C++ implementation by .

  • Simple Network Simulator and Board Files

    Daniel04/28/2017 at 01:00 0 comments

    I've added a link to the mesh source code so far and to the board files. To validate the idea, I've wrapped the Open Mesh implementation of the trickle algorithm in Python and have written a rudimentary event queue based network simulator. The network simulator shows how values travel between nodes over time. They do indeed hop from node to node and eventually become synchronized everywhere.

    The case I was most interested in understanding is what will happen when the network is 'full', that is, when nodes cannot hold all the values that are currently being transmitted through the network. When this happens, a 'full' node might rapidly retransmit every new item it receives, wasting power; it could choose to forget newer values, or older values, or random values. The right choice will be a tradeoff between reachability and power consumption. The best option I've found so far seems to be to slow down the retransmission rate of every value on the node when a new value would take it over capacity. It might be possible to transmit more data than an individual node can hold at once by spreading the load out over time.

    It will be important to handle a full network gracefully, but recall that the network is not likely to be full before you have a couple dozen nodes. If that happens you would want to partition the network into multiple separate meshes.

    The second part of the source is a re-orderable priority queue plus key / value lookup data structure. The mesh network is always checking for the next expired message (values are retransmitted on timeout) and must be able to change their priority when it hears the same value on the network. The priority queue makes it very efficient to find the next item to retransmit, but normally does not allow re-ordering. Our priority queue maintains a sorted list of keys, for quick, memory efficient binary search to compare against incoming values, and maintains backlinks from the keys to their position in the priority queue. Combined we can efficiently search for values by key, change their priority, and update their position in the priority queue.

    I've also been able to make a memory improvement to the OpenMesh trickle structure. The timeouts are always (minimum_timeout * (2**n)). The original code uses 13 bytes to store an instance of the trickle algorithm, storing (2**n) in a uint32_t, but we save 3 bytes per trickle by only storing n in a uint8_t.

    The source repository also includes the Kicad board files for the pictured node.

  • Part Showcase: JST-PH Connectors

    Daniel04/17/2017 at 01:52 0 comments

    This board features both Micro-USB and JST-PH power connectors, depending on whether you want to use a battery, but you must not connect them both at the same time. The through-hole JST-PH connector is also more firmly attached to the board than the Micro-USB. In an attempt to be compatible with Adafruit batteries, the ground pin is on the right when looking into the right-angle header.

    These connectors and the larger JST-XH connectors are very popular but were a bit of a mystery. You buy them directly from JST. They are cheap. A couple of weeks later you have a little box of plastic and metal pieces. To make a connection you need the matching header, housing, and contacts. The header goes on the board, the contacts are crimped onto your wires, and clip permanently into the housing. You cannot make a proper crimp with pliers; you need a crimping tool. You can buy one from JST for about $489.89 but I bought this one. However you might want to look for one that is also compatible with slightly larger connectors.

    Happily it appears that since the last time I looked JST's connectors are also available on Digikey. It's worth having a box or two of these around for whenever you need to make a wire to board connection.

  • Part Showcase: Cree CLV1A

    Daniel04/17/2017 at 01:11 0 comments

    This board has a nifty little RGB LED called the Cree CLV1A. It's a 4-pin SMD part in what's called a 4-PLCC package. It looks like they are designed for video walls, but they also make great little indicators. The main problem is that they are way too bright at 20mA. On a previous project I used a small square of coroplast (plastic cardboard) as a diffuser to avoid blinding myself, lately I just put in much higher value (e.g. 180 Ohm) resistors.

    The other problem with the CLV1A is that they are a bit expensive. The next board design will probably spec in several individual SMD LEDs, available in bulk for next to nothing.

  • The third one works

    Daniel04/17/2017 at 00:59 0 comments

    The pictured board is my third attempt to assemble a working unit. After the first one didn't work, I got discouraged for quite some time. The second board was coming along nicely, but an overzealous application of a heat gun formed a bubble in the solder mask, lifting the parts off in a wave. It probably doesn't work. Then the third one was gently assembled with a more relaxed 325 degree iron temperature, first with the MCU rotated 90 degrees, second with it placed correctly, and now it is working great.

    Lessons learned include putting the largest orientation marker you can afford on the soldermask layer of your footprints. Also, it took a long time to get the programmer working correctly. It's still possible that board #1 actually works, just the programmer wasn't able to connect.

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Wassim wrote 2 days ago point

Hello,

I really like this project although it might be hard to grasp the added value which is the low power listening, for a low power mesh network. It is very much complementary to my project #Home Smart Mesh , where I worked around this by splitting into two types of nodes, ultra-low power, that wake up rarely, randomly and talk once, and full powered nodes as mesh repeaters that listen all the time. My sensor tags use STM8L, I already planned the STM32 transition and they're sleeping unused on my shelves, I got the STM32L062K8T which I would highly recommend for you as well, as it has two main improvement over the F051, it goes down to lower voltage 1.65 V and not 2.0 V, and has embedded AES for who knows future bits of security.

Same as you, I'm interfacing with MQTT, I optionally use json for the complex messages, non time-series based, but I went for a binary protocol at RF level, that does not prevent repeaters from being agnostic to the payload content, the users have to implement the handling anyway. As an example I can update my 8 channel dimmer for all channels 16 bit values in a single packet.

There's really room for collaboration here if you're interested.

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