The TOFFEE Project :: Documentation

This is my next software development update of TOFFEE-DataCenter which I am working since past few weeks. I was very busy in implementing the core TOFFEE-DataCenter components along with prototyping, benchmarking, implementing and testing the same. However today is the first time ever I did a fresh new CLI interface for the upcoming new TOFFEE-DataCenter.

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).

Demo TOFFEE_DataCenter WAN Optimization VM (in VirtualBox) Test Setup

Here is my VLOG Youtube video of the same which includes details about version release notes, future road-map and so on. The TOFFEE release is highly optimized and customized for hardware platforms such as x86-64 based Intel NUC and other Intel mobile computing platforms such as laptops and so on. This version (or release) is not suited and so not recommended to be used for high-end desktop and server hardware platform.

Network MTU research and optimization of WAN Links

TOFFEE-Butterscotch a TOFFEE for Home/SOHO Internet/WAN bandwidth

TOFFEE can be used to optimize expensive Wireless backhaul network infrastructure. TOFFEE can be deployed over existing slow or often outdated old backhaul networks too. This will leverage mobile ISPs and network service providers to reduce their bulk IT CapEx and OpEx Costs.

Earlier the TOFFEE is intended to work on IoT devices, Satellite Networks, branch office/SOHO deployments. In most cases the users may deploy just one or couple of TOFFEE devices per site. But in the case of TOFFEE-DataCenter, users can scale-up deploying the same in multiple servers in a sort of distributed cluster computing scenario. Besides the core TOFFEE-DataCenter components (such as packet processing engine/framework), I need to do lot of changes in its Graphical User Interface (GUI) too to address these new requirements.

LoRaWAN - Network Optimization via TOFFEE WAN Optimization

When you are dealing Deep Space Networks (DSN) one among the most challenging parts is the Interplanetary distances and communicating data across such vast distances. This is where we are not dealing with common Internet type traffic such as HTTP/FTP/VoIP/etc but it is completely different when it comes to DSN so far. So optimizing data in DSN becomes mandatory. For example if you think one of the Mars Rovers, they have used LZO lossless compression.