Amanda Ghassaei, who has this amazing project I just found out about, also has a great Instructable for doing DSP with Arduino. A few hours and one blown op-amp later, I was able to get my Arduino to pickup my bass playing. It samples around 38.5 kHz, but I only had it send serial data back every 10 ms (a measly 100 Hz). Still, I was able to generate this graph with the data. You can see the clipping where I cranked it up to test the peak indicator LED.
The atmega328 has 32Kb flash memory. If I used half of that for a delay line, 16,000 samples / 38500 samples/sec = .42 second delay. I could get a longer delay by using external flash (e.g. SD card), but I worry that the read/write time would be low. It will be interesting to apply some of the concepts from class to actual signals. What does a 50-point averager do to my tone? (answer: probably reverb)
There's not a lot I can do with this now, since I can't hear the results of any processing yet. I just ordered a DAC0808 8-bit digital-analog converter. (The new DUE has two built-in DAC outputs, as well as PWM, although it still isn't an ideal platform for DSP). Eventually, I would like to get an FFT algorithm running and make a tuner. That will probably have to wait until after finals, though.
EDIT: Just found out about wki.pe/Resistor_ladder s.
Tuesday, April 30, 2013
Monday, April 1, 2013
Location-enabled mesh networking protocol
Think of a peer-to-peer network. Not in an application-level sense, like torrents or Bitcoin, but on a physical/data-link level. Rather than connecting to a router, your device connects directly to a handful of other nearby devices, creating a web of communication. Mesh network topologies are not a new concept. Problems such as high latency and potentially different hardware have limited usage to a few novel solutions. But these protocols lack a powerful tool that is quickly coming ubiquitous as we approach the Internet of Things, and that is location data.
Devices that require network connectivity are increasingly mobile. It is expected that networked mobile devices will include compass/gyroscope/accelerometer/GPS hardware, which in combination can give the location and heading information (position, velocity, and acceleration) of those devices. In an ad-hoc mesh network, the number of connections each node can make is limited, and creating new connections is expensive. Using this information, devices could make smart decisions about what connections to make. If a node is moving quickly away from you, the value of making a connection to it is low, as it will be out of range in a short amount of time.
A mesh network should be a preferred topology for IoT. It is cheap to implement, free of authority, and mirrors social interaction. Take, for example, a system of smart cars. To avoid collisions, the smart cars must be able to communicate with those nearby. Using our current system, each device would require a network connection such as LTE. The communications would pass up to a nearby router/server and back down to the nearby vehicles. This method has three flaws. First, it is inefficient. Direct connections to nearby vehicles would increase the rate of data transfer, and even connections that require a low number of hops would about equal the transfer rate of a router system. It is also expensive. Having high-speed, reliable dedicated routers capable of covering the entire road system of a country is quite a demand, and installing and supporting this expensive hardware would be even more burdensome. The slow and uneven deployment of broadband in America shows the extreme cost and difficulty of this. Finally, they are insecure, in that they offer a single point of failure. If an attacker were to disable the router, communication between the vehicles would be lost, with potentially catastrophic results. A distributed network lacks authority making it resilient against attacks. The network is able to quickly adapt to the loss of a single node.
A distributed network like this is not without its security problems. For example, a person sending false positioning data could reduce or possibly even disable the network by skewing the calculations of optimal connections. This is analogous to (but distinct from) the problem of, in the car example, someone standing on the sidewalk, claiming to be a car about to fly across the street, potentially causing a collision between the real cars as they react to this false threat. This is part of the security trade-off of authority-less networks, and is ultimately a problem to be solved in the field of network security. This does not diminish the value of a location-enabled mesh networking protocol.
Edit:
Turns out much of this already exists. wki.pe/Intelligent_Vehicular_AdHoc_Network specifically mentions wki.pe/Position-based_routing . Other cool stuff I found:
http://wirelessafrica.meraka.org.za/wiki/index.php/DIY_Mesh_Guide
wki.pe/Netsukuku
wki.pe/Babel_(protocol)
Edit:
Turns out much of this already exists. wki.pe/Intelligent_Vehicular_AdHoc_Network specifically mentions wki.pe/Position-based_routing . Other cool stuff I found:
http://wirelessafrica.meraka.org.za/wiki/index.php/DIY_Mesh_Guide
wki.pe/Netsukuku
wki.pe/Babel_(protocol)
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