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LoRaWAN - Network Optimization via TOFFEE WAN Optimization

Here is my power-consumption measurements of various devices deployed within my home lab. I measured via my kill-a-watt sort of power-meter which is fairly reliable and accurate. I checked its accuracy with various standard load such as Philips LED laps and other constant power-consuming devices to make sure that the power-meter is precise.

Today I finally completed building my own private CDN. As I discussed so far in my earlier topics (Building my own CDN), I want to custom build the same step-by-step from scratch. And I don't want to for now use/buy third-party CDN subscriptions from Akamai, CloudFlare, Limelight, etc as I discussed earlier.

In the previous update (17-Jun-2016) I discussed about the upcoming new Random Packet drop feature along with other completed features. Now I completed the entire TOFFEE-Mocha Random packet drop feature. I completed all the kernel components and the UI support of the same. And to make GUI settings more organized I split the earlier Basic-Settings page into two separate pages namely: Packet Drop and Packet Delay. So this way it is simple to understand settings according to their functionality.

I always wanted to do some real experiments and research on packet flow patterns from High-bandwidth to Low-bandwidth networks via networking devices. This is something can be analyzed via capturing Network stack buffer data and other parameters, bench-marking, and so on. But eventually the data-transfer nature and other aspects is often contaminated due to the underlying OS and the way Network stack is implemented. So to understand the nature of packet flow from Higher to Lower bandwidth and vice-versa such as Lower to higher bandwidth, I thought I experiment with various tools and things which physically we can observe this phenomena.

You can build a basic TOFFEE WAN Optimization hardware completely in software layer (i.e its networking data-plane and control-plane). And if you are a product manufacturer you can make commercial WAN Optimization products with TOFFEE with software layer alone. And if you choose to improve its performance, you can use any third-party PCIe Compression Accelerator cards.

Ever since after I launched my new The TOFFEE Project website on 1-May'2016, I can see there is a steep increase in traffic. Soon after the launch when I monitored its Alexa rankings it was reporting about 12 Million or so. But once it is getting more and more traffic the Alexa rankings shot up and now currently it shows around 2 Million (as on 22-July-2016). Alexa is an excellent tool to monitor your overall website global ranking and indirectly its performance. Unlike Google Analytics which is bound one or other way into Google's SEO. Alexa gives you a second opinion about your website's growth.

Today I got a feature request from Jonathan Withers. Jonathan is from a company called MultiWave Australia. He said he is able to get the TOFFEE-Mocha Raspberry Pi setup up and with that he is able to emulate geostationary satellite link. But he requested me is there a way to extend the constant packet delay from 40mS to 500mS. So as a part of his request I supported the same in the current ongoing development version of TOFFEE-Mocha.

Bitcoin Mining - Blockchain Technology - Network Optimization via TOFFEE Data-Center WAN Optimization

Ever since after I launched my new The TOFFEE Project website on 1-May'2016, I can see there is a steep increase in traffic. Soon after the launch when I monitored its Alexa rankings it was reporting about 12 Million or so. But once it is getting more and more traffic the Alexa rankings shot up and now currently it shows around 2 Million (as on 22-July-2016). Alexa is an excellent tool to monitor your overall website global ranking and indirectly its performance. Unlike Google Analytics which is bound one or other way into Google's SEO. Alexa gives you a second opinion about your website's growth.

TOFFEE-Butterscotch Documentation :: TOFFEE-Butterscotch-1.0.11-rpi2-23-nov-2016