Documentation :: Documentation :: TOFFEE-Mocha - WAN Emulator

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.

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.

WAN Network data can be optimized at various levels depending upon the network applications, protocols, topology and use-cases. So the amount of data you can optimize will depend on the strategy you choose to optimize. Such as: Network Packet level optimization, Session level optimization, File level optimization, etc.

Today I refined the first page consolidated report graphs. TOFFEE-Mocha (unlike TOFFEE) is a WAN Emulator, so the graphs are supposed to highlight this purpose and should display the overall network activity. Unlike TOFFEE, the TOFFEE-Mocha report should contain in general what is received versus what is sent across the wire. In case if the packet drop feature is enabled, you should see few missing bytes and packets. Similarly in future I may support packet duplication feature, in that case you may see more packets/bytes sent versus the packets/bytes actually received.

One of the suggestions Google PageSpeed Insights tool suggested for The TOFFEE Project website is to minify the css and java script files. Minify Script files: When you read online about minification of your web script files, often they highlight file size savings and thus resulting faster download time and better website performance.

LoRaWAN - Network Optimization via TOFFEE WAN Optimization

Large Infrastructure or ISP setup: In case if you are an ISP and interested in deploying a large customer WAN Optimized network or an add-on enhanced (WAN Optimized) network for select few customers, then you can deploy something as shown below. Although this case is not meant for hobby/DIY users. This is a feasible solution for high-end professional application and the same can be deployed.

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.

LoRaWAN - Network Optimization via TOFFEE WAN Optimization

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.

TOFFEE TOFFEE Data-Center is specifically meant for Data Center, Cluster Computing, HPC applications. TOFFEE is built in Linux Kernel core. This makes it inflexible to adapt according to the hardware configuration. It does sequential packet processing and does not scale up well in large multi-core CPU based systems (such as Intel Xeon servers, Core i7 Extreme Desktop systems,etc). Apart from this since it is kernel based, if there is an issue in kernel, it may crash entire system. This becomes a challenge for any carrier grade equipment (CGE) hardware build.

In case if you need to deploy TOFFEE along with your existing VPN devices you can deploy the same as shown below. This will allow your VPN devices to encrypt your TOFFEE WAN Optimized network data. NOTE: Make sure about the VPN deployment topology done in the right order. Else TOFFEE (LAN side) may get VPN encrypted packets which may not be possible (and or difficult) to further optimize. Hence always make sure to deploy them in a topology suggested below so that TOFFEE devices are out of VPN tunnel.

VPN Networks may degrade network performance due to various packet processing overheads such as encryption and by adding extra network protocol header(s) (such as IPv4/IPv6, IPSec, etc). This may inflate near MTU sized packets and causes excessive packet fragmentation. Here are the few examples of packet processing involved in a VPN (or a VPN like) Tunnel. With TOFFEE you can optimize these packets even before they get processed on to a VPN device. TOFFEE optimizes packet contents (application payload and transport headers) so that these TOFFEE optimized packets when they get processed by VPN devices (or VPN software stack) they may never need further packet fragmentation. Here is a deployment scenario of TOFFEE with VPN devices.

Here is my video article on Network Latency in WAN Networks (such as long distance Satellite links, etc) and how you can optimize the same to achieve better network performance.