DOCUMENTATION 》 Network Latency and Bandwidth Assessment - for Network Admins and Infrastructure Architects

LoRaWAN - Network Optimization via TOFFEE WAN Optimization

As a research experiment I replaced my Intel Core i7 5820K desktop PC with my Intel Celeron 1037U Mini-PC as my everyday desktop system. This is an attempt to reduce my overall monthly power consumption. As well an attempt to do feasibility tests and research to know how far Mini PC will dominate the market in future and to study the real potential of Mini PCs.

I was doing some specific tests in my TOFFEE and TOFFEE-DataCenter (WAN optimization) scenarios such as variable upload and download speeds. And I was also doing some experiments with speedtest.net and I did some of these tests with TOFFEE-Mocha. I realized there is a case that I can introduce asymmetric constant delays so that you can get different download speed and a different upload speed. And in some cases much faster download speeds and relatively slower upload speeds.

Here is my first software development update of TOFFEE-Butterscotch. In my first TOFFEE-Butterscotch news update I have introduced about TOFFEE-Butterscotch research, project specifications, use-cases, etc. Introducing TOFFEE-Butterscotch Alerts: These are simple packet counters which corresponds to the filter type. For example if the incoming TCP-SYN packets are blocked then its corresponding alert counter will increment whenever such a packet arrives and gets filtered (dropped).

Assume you have two sites (such as Site-A and Site-B) connected via slow/critical WAN link as shown below. You can optimize this link by saving the bandwidth as well possibly improve the speed. However, the WAN speed can be optimized only if the WAN link speeds are below that of the processing latency of your TOFFEE installed hardware. Assume your WAN link is 12Mbps, and assume the maximum WAN optimization speed/capacity of Raspberry Pi is 20Mbps, then your link will get speed optimization too. And in another case, assume your WAN link is 50Mbps, then using the Raspberry Pi as WAN Optimization device will actually increase the latency (i.e slows the WAN link). But in all the cases the bandwidth savings should be the same irrespective of the WAN link speed. In other words, if you want to cut down the WAN link costs via this WAN Optimization set up, you can always get it since it reduces the overall bandwidth in almost all the cases (including encrypted and pre-compressed data).

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.

Network MTU research and optimization of WAN Links

I started working on the new TOFFEE project (which is the fork of my earlier TrafficSqueezer open-source project) starting from 1st January 2016 onwards. Ever since I was busy in research and altering certain old features so that it is more minimal than TrafficSqueezer, a more focused agenda, deliver refined code and a broader vision. I have lined up more things to follow in the upcoming months. I want to focus about all aspects of WAN communication technologies not just on core WAN Optimization research and technology.

When you choose to use your Raspberry Pi device as your IoT based remote weather station or if you are building Linux kernel (like kernel compilation) within the same, you need a good uninterrupted power source (UPS). But if you are using it on site or in some research camping location you can choose to power your Raspberry Pi device with your custom off-grid solar power source.

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.

Today I have done a test setup so that I can able to connect my Android Samsung Tab via TOFFEE DataCenter. Below is my complete test topology of my setup. For demo (and research/development) context I configured TOFFEE DataCenter in engineering debug mode. So that I do not need two devices for this purpose.